Package com.google.ortools.sat
Class SatParameters.Builder
java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderType>
com.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
com.google.ortools.sat.SatParameters.Builder
- All Implemented Interfaces:
SatParametersOrBuilder,com.google.protobuf.Message.Builder,com.google.protobuf.MessageLite.Builder,com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder,Cloneable
- Enclosing class:
SatParameters
public static final class SatParameters.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
implements SatParametersOrBuilder
Contains the definitions for all the sat algorithm parameters and their default values. NEXT TAG: 223Protobuf type
operations_research.sat.SatParameters-
Method Summary
Modifier and TypeMethodDescriptionaddAllExtraSubsolvers(Iterable<String> values) A convenient way to add more workers types.addAllIgnoreSubsolvers(Iterable<String> values) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.addAllRestartAlgorithms(Iterable<? extends SatParameters.RestartAlgorithm> values) The restart strategies will change each time the strategy_counter is increased.addAllSubsolverParams(Iterable<? extends SatParameters> values) It is possible to specify additional subsolver configuration.addAllSubsolvers(Iterable<String> values) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.addExtraSubsolvers(String value) A convenient way to add more workers types.addExtraSubsolversBytes(com.google.protobuf.ByteString value) A convenient way to add more workers types.addIgnoreSubsolvers(String value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.addIgnoreSubsolversBytes(com.google.protobuf.ByteString value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) The restart strategies will change each time the strategy_counter is increased.addSubsolverParams(int index, SatParameters value) It is possible to specify additional subsolver configuration.addSubsolverParams(int index, SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.addSubsolverParams(SatParameters value) It is possible to specify additional subsolver configuration.addSubsolverParams(SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.addSubsolverParamsBuilder(int index) It is possible to specify additional subsolver configuration.addSubsolvers(String value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.addSubsolversBytes(com.google.protobuf.ByteString value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.build()clear()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.Whether we generate and add Chvatal-Gomory cuts to the LP at root node.Whether we generate clique cuts from the binary implication graph.For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.Whether we generate MIR cuts at root node.When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.Whether we generate Zero-Half cuts at root node.When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.optional double blocking_restart_multiplier = 66 [default = 1.4];optional int32 blocking_restart_window_size = 65 [default = 5000];A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.Clause activity parameters (same effect as the one on the variables).All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];Trigger a cleanup when this number of "deletable" clauses is learned.optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.During a cleanup, we will always keep that number of "deletable" clauses.Temporary flag util the feature is more mature.Whether or not the assumption levels are taken into account during the LBD computation.If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.Whether we presolve the cp_model before solving it.How much effort do we spend on probing.Whether we also use the sat presolve when cp_model_presolve is true.optional double cut_active_count_decay = 156 [default = 0.8];Target number of constraints to remove during cleanup.Control the global cut effort.These parameters are similar to sat clause management activity parameters.Crash if we do not manage to complete the hint into a full solution.If positive, try to stop just after that many presolve rules have been applied.We have two different postsolve code.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.If true, it disable all constraint expansion.If true, registers more lns subsolvers with different parameters.Whether we enumerate all solutions of a problem without objective.If true, expand all_different constraints that are not permutations.If true and the Lp relaxation of the problem has a solution, try to exploit it.optional bool exploit_all_precedences = 220 [default = false];When branching on a variable, follow the last best solution value.If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.When branching on a variable, follow the last best relaxation solution value.A convenient way to add more workers types.clearField(com.google.protobuf.Descriptors.FieldDescriptor field) If true, the final response addition_solutions field will be filled with all solutions from our solutions pool.If true, add information about the derived variable domains to the CpSolverResponse.Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.If true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];optional double glucose_decay_increment = 23 [default = 0.01];optional int32 glucose_decay_increment_period = 24 [default = 5000];The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.Conflict limit used in the phase that exploit the solution hint.If true, we don't keep names in our internal copy of the user given model.Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];The initial value of the variables activity.If true, the solver will add a default integer branching strategy to the already defined search strategy.optional int32 interleave_batch_size = 134 [default = 1];Experimental.If true, we disable the presolve reductions that remove feasible solutions from the search space.A non-negative level indicating the type of constraints we consider in the LP relaxation.Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing).Add a prefix to all logs.Whether the solver should log the search progress.Whether the solver should display per sub-solver search statistics.Log to response proto.Log to stdout.Cut generator for all diffs can add too many cuts for large all_diff constraints.optional double max_clause_activity_value = 18 [default = 1e+20];If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.Max number of time we perform cut generation and resolve the LP at level 0.Maximum time allowed in deterministic time to solve a problem.When loading a*x + b*y ==/!= c when x and y are both fully encoded.In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).Maximum memory allowed for the whole thread containing the solver.Maximum number of conflicts allowed to solve a problem.The limit on the number of cuts in our cut pool.In case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];Maximum time allowed in seconds to solve a problem.optional double max_variable_activity_value = 16 [default = 1e+100];optional double merge_at_most_one_work_limit = 146 [default = 100000000];During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];Whether we use a simple heuristic to try to minimize an UNSAT core.A different algorithm during PB resolution.optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization.If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread.While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.If true, some continuous variable might be automatically scaled.As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.All continuous variable of the problem will be multiplied by this factor.When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.Add that many lazy constraints (or cuts) at once in the LP.After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.optional int32 num_search_workers = 100 [default = 0];Specify the number of parallel workers (i.e.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) For the cut that can be generated at any level, this control if we only try to generate them at the root node.If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.This has no effect if optimize_with_core is false.Same as for the clauses, but for the learned pseudo-Boolean constraints.optional double pb_cleanup_ratio = 47 [default = 0.5];optional bool permute_presolve_constraint_order = 179 [default = false];This is mainly here to test the solver variability.If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".A few presolve operations involve detecting constraints included in other constraint.The maximum "deterministic" time limit to spend in probing.How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.Whether or not we use Bounded Variable Addition (BVA) in the presolve.If set at zero (the default), it is disabled.Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.The solver ignores the pseudo costs of variables with number of recordings less than this threshold.A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.Randomize fixed search.The proportion of polarity chosen at random.At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.optional double relative_gap_limit = 160 [default = 0];If true, the solver tries to repair the solution given in the hint.The restart strategies will change each time the strategy_counter is increased.In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.optional double restart_lbd_average_ratio = 71 [default = 1];Restart period for the FIXED_RESTART strategy.Size of the window for the moving average restarts.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];Search randomization will collect equivalent 'max valued' variables, and pick one randomly.Allows sharing of new learned binary clause between workers.Allows sharing of the bounds of modified variables at level 0.Allows objective sharing between workers.Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.Size of the top-n different solutions kept by the solver.For an optimization problem, stop the solver as soon as we have a solution.Mainly used when improving the presolver.The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.It is possible to specify additional subsolver configuration.In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.Whether we try to automatically detect the symmetries in a model and exploit them.How much we try to "compress" a table constraint.optional bool use_absl_random = 180 [default = false];Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.The solver usually exploit the LP relaxation of a model.Adds a feasibility pump subsolver along with lns subsolvers.If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.Stores and exploits "implied-bounds" in the solver.LNS parameters.For an optimization problem, whether we follow some hints in order to find a better first solution.If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.Whether to use pseudo-Boolean resolution to analyze a conflict.If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.If true, search will continuously probe Boolean variables, and integer variable bounds.Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.Turns on relaxation induced neighborhood generator.optional bool use_sat_inprocessing = 163 [default = false];Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.Each time a conflict is found, the activities of some variables are increased by one.clone()doubleStop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.booleanWhether we generate and add Chvatal-Gomory cuts to the LP at root node.booleanWhether we generate clique cuts from the binary implication graph.booleanFor the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.booleanIf true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.booleanWhether we generate MIR cuts at root node.booleanWhen the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.booleanWhether we generate Zero-Half cuts at root node.booleanWhen this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.booleanIf true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];intIf non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.doubleoptional double blocking_restart_multiplier = 66 [default = 1.4];intoptional int32 blocking_restart_window_size = 65 [default = 5000];intA non-negative level indicating how much we should try to fully encode Integer variables as Boolean.booleanIndicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.doubleClause activity parameters (same effect as the one on the variables).intAll the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];intTrigger a cleanup when this number of "deletable" clauses is learned.optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];doubleDuring a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.intDuring a cleanup, we will always keep that number of "deletable" clauses.booleanTemporary flag util the feature is more mature.booleanWhether or not the assumption levels are taken into account during the LBD computation.booleanIf true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.booleanWhether we presolve the cp_model before solving it.intHow much effort do we spend on probing.booleanWhether we also use the sat presolve when cp_model_presolve is true.doubleoptional double cut_active_count_decay = 156 [default = 0.8];intTarget number of constraints to remove during cleanup.intControl the global cut effort.doubleThese parameters are similar to sat clause management activity parameters.booleanCrash if we do not manage to complete the hint into a full solution.intIf positive, try to stop just after that many presolve rules have been applied.booleanWe have two different postsolve code.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];com.google.protobuf.ByteStringoptional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];static final com.google.protobuf.Descriptors.Descriptorcom.google.protobuf.Descriptors.DescriptorbooleanIf true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.booleanIf true, it disable all constraint expansion.booleanIf true, registers more lns subsolvers with different parameters.booleanWhether we enumerate all solutions of a problem without objective.booleanIf true, expand all_different constraints that are not permutations.booleanIf true and the Lp relaxation of the problem has a solution, try to exploit it.booleanoptional bool exploit_all_precedences = 220 [default = false];booleanWhen branching on a variable, follow the last best solution value.booleanIf true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.booleanWhen branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.booleanWhen branching on a variable, follow the last best relaxation solution value.getExtraSubsolvers(int index) A convenient way to add more workers types.com.google.protobuf.ByteStringgetExtraSubsolversBytes(int index) A convenient way to add more workers types.intA convenient way to add more workers types.com.google.protobuf.ProtocolStringListA convenient way to add more workers types.booleanIf true, the final response addition_solutions field will be filled with all solutions from our solutions pool.booleanIf true, add information about the derived variable domains to the CpSolverResponse.booleanWhether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.booleanIf true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];doubleoptional double glucose_decay_increment = 23 [default = 0.01];intoptional int32 glucose_decay_increment_period = 24 [default = 5000];doubleThe activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.intConflict limit used in the phase that exploit the solution hint.booleanIf true, we don't keep names in our internal copy of the user given model.getIgnoreSubsolvers(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.com.google.protobuf.ByteStringgetIgnoreSubsolversBytes(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.intRather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.com.google.protobuf.ProtocolStringListRather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];doubleThe initial value of the variables activity.booleanIf true, the solver will add a default integer branching strategy to the already defined search strategy.intoptional int32 interleave_batch_size = 134 [default = 1];booleanExperimental.booleanIf true, we disable the presolve reductions that remove feasible solutions from the search space.intA non-negative level indicating the type of constraints we consider in the LP relaxation.doubleIndicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing).Add a prefix to all logs.com.google.protobuf.ByteStringAdd a prefix to all logs.booleanWhether the solver should log the search progress.booleanWhether the solver should display per sub-solver search statistics.booleanLog to response proto.booleanLog to stdout.intCut generator for all diffs can add too many cuts for large all_diff constraints.doubleoptional double max_clause_activity_value = 18 [default = 1e+20];intIf a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.intMax number of time we perform cut generation and resolve the LP at level 0.doubleMaximum time allowed in deterministic time to solve a problem.intWhen loading a*x + b*y ==/!= c when x and y are both fully encoded.intIn the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).longMaximum memory allowed for the whole thread containing the solver.longMaximum number of conflicts allowed to solve a problem.intThe limit on the number of cuts in our cut pool.intIn case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];booleanIf true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];doubleMaximum time allowed in seconds to solve a problem.doubleoptional double max_variable_activity_value = 16 [default = 1e+100];doubleoptional double merge_at_most_one_work_limit = 146 [default = 100000000];doubleDuring presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];booleanWhether we use a simple heuristic to try to minimize an UNSAT core.booleanA different algorithm during PB resolution.intoptional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];intParameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization.intIf there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread.doubleWhile adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.booleanIf true, some continuous variable might be automatically scaled.doubleAs explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.booleanEven if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.intTo avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.doubleWe need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.doubleAny finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.doubleAll continuous variable of the problem will be multiplied by this factor.doubleWhen scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.doubleoptional double model_reduction_log_frequency_in_seconds = 218 [default = 5];getName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.com.google.protobuf.ByteStringIn some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.intAdd that many lazy constraints (or cuts) at once in the LP.intAfter each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.intoptional int32 num_search_workers = 100 [default = 0];intSpecify the number of parallel workers (i.e.booleanFor the cut that can be generated at any level, this control if we only try to generate them at the root node.booleanIf one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.booleanThe default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.booleanDo a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.booleanThis has no effect if optimize_with_core is false.intSame as for the clauses, but for the learned pseudo-Boolean constraints.doubleoptional double pb_cleanup_ratio = 47 [default = 0.5];booleanoptional bool permute_presolve_constraint_order = 179 [default = false];booleanThis is mainly here to test the solver variability.intIf non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.booleanWhether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];booleanWhether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.intApply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.intDuring presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.intDuring presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.booleanIf true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".longA few presolve operations involve detecting constraints included in other constraint.doubleThe maximum "deterministic" time limit to spend in probing.intHow much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.booleanWhether or not we use Bounded Variable Addition (BVA) in the presolve.longIf set at zero (the default), it is disabled.doubleSome search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.longThe solver ignores the pseudo costs of variables with number of recordings less than this threshold.doubleA number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.booleanRandomize fixed search.doubleThe proportion of polarity chosen at random.intAt the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.doubleoptional double relative_gap_limit = 160 [default = 0];booleanIf true, the solver tries to repair the solution given in the hint.getRestartAlgorithms(int index) The restart strategies will change each time the strategy_counter is increased.intThe restart strategies will change each time the strategy_counter is increased.The restart strategies will change each time the strategy_counter is increased.doubleIn the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.doubleoptional double restart_lbd_average_ratio = 71 [default = 1];intRestart period for the FIXED_RESTART strategy.intSize of the window for the moving average restarts.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];longSearch randomization will collect equivalent 'max valued' variables, and pick one randomly.booleanAllows sharing of new learned binary clause between workers.booleanAllows sharing of the bounds of modified variables at level 0.booleanAllows objective sharing between workers.doubleSpecifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.intSize of the top-n different solutions kept by the solver.booleanFor an optimization problem, stop the solver as soon as we have a solution.booleanMainly used when improving the presolver.doubleThe parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.getSubsolverParams(int index) It is possible to specify additional subsolver configuration.getSubsolverParamsBuilder(int index) It is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.intIt is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.getSubsolverParamsOrBuilder(int index) It is possible to specify additional subsolver configuration.List<? extends SatParametersOrBuilder>It is possible to specify additional subsolver configuration.getSubsolvers(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.com.google.protobuf.ByteStringgetSubsolversBytes(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.intIn multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.com.google.protobuf.ProtocolStringListIn multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.booleanAt a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.intWhether we try to automatically detect the symmetries in a model and exploit them.intHow much we try to "compress" a table constraint.booleanoptional bool use_absl_random = 180 [default = false];booleanBlock a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.booleanIf true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.booleanThis can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.booleanWhen this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.booleanWhen set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.booleanWhen this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.booleanWhether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.booleanThe solver usually exploit the LP relaxation of a model.booleanAdds a feasibility pump subsolver along with lns subsolvers.booleanIf true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.booleanStores and exploits "implied-bounds" in the solver.booleanLNS parameters.booleanFor an optimization problem, whether we follow some hints in order to find a better first solution.booleanIf true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.booleanWhen this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.booleanWhether to use pseudo-Boolean resolution to analyze a conflict.booleanIf this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().booleanWhen this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.booleanIf true, search will continuously probe Boolean variables, and integer variable bounds.booleanTurns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.booleanTurns on relaxation induced neighborhood generator.booleanoptional bool use_sat_inprocessing = 163 [default = false];booleanAdd a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.booleanWhen this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.booleanWhen this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.doubleEach time a conflict is found, the activities of some variables are increased by one.booleanStop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.booleanWhether we generate and add Chvatal-Gomory cuts to the LP at root node.booleanWhether we generate clique cuts from the binary implication graph.booleanFor the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.booleanIf true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.booleanWhether we generate MIR cuts at root node.booleanWhen the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.booleanWhether we generate Zero-Half cuts at root node.booleanWhen this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.booleanIf true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.booleanoptional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];booleanIf non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.booleanoptional double blocking_restart_multiplier = 66 [default = 1.4];booleanoptional int32 blocking_restart_window_size = 65 [default = 5000];booleanA non-negative level indicating how much we should try to fully encode Integer variables as Boolean.booleanIndicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.booleanClause activity parameters (same effect as the one on the variables).booleanAll the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.booleanoptional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];booleanTrigger a cleanup when this number of "deletable" clauses is learned.booleanoptional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];booleanDuring a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.booleanDuring a cleanup, we will always keep that number of "deletable" clauses.booleanTemporary flag util the feature is more mature.booleanWhether or not the assumption levels are taken into account during the LBD computation.booleanIf true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.booleanWhether we presolve the cp_model before solving it.booleanHow much effort do we spend on probing.booleanWhether we also use the sat presolve when cp_model_presolve is true.booleanoptional double cut_active_count_decay = 156 [default = 0.8];booleanTarget number of constraints to remove during cleanup.booleanControl the global cut effort.booleanThese parameters are similar to sat clause management activity parameters.booleanCrash if we do not manage to complete the hint into a full solution.booleanIf positive, try to stop just after that many presolve rules have been applied.booleanWe have two different postsolve code.booleanoptional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];booleanIf true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.booleanIf true, it disable all constraint expansion.booleanIf true, registers more lns subsolvers with different parameters.booleanWhether we enumerate all solutions of a problem without objective.booleanIf true, expand all_different constraints that are not permutations.booleanIf true and the Lp relaxation of the problem has a solution, try to exploit it.booleanoptional bool exploit_all_precedences = 220 [default = false];booleanWhen branching on a variable, follow the last best solution value.booleanIf true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.booleanWhen branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.booleanWhen branching on a variable, follow the last best relaxation solution value.booleanIf true, the final response addition_solutions field will be filled with all solutions from our solutions pool.booleanIf true, add information about the derived variable domains to the CpSolverResponse.booleanWhether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.booleanIf true, variables appearing in the solution hints will be fixed to their hinted value.booleanoptional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];booleanoptional double glucose_decay_increment = 23 [default = 0.01];booleanoptional int32 glucose_decay_increment_period = 24 [default = 5000];booleanThe activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.booleanConflict limit used in the phase that exploit the solution hint.booleanIf true, we don't keep names in our internal copy of the user given model.booleanoptional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];booleanThe initial value of the variables activity.booleanIf true, the solver will add a default integer branching strategy to the already defined search strategy.booleanoptional int32 interleave_batch_size = 134 [default = 1];booleanExperimental.booleanIf true, we disable the presolve reductions that remove feasible solutions from the search space.booleanA non-negative level indicating the type of constraints we consider in the LP relaxation.booleanIndicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing).booleanAdd a prefix to all logs.booleanWhether the solver should log the search progress.booleanWhether the solver should display per sub-solver search statistics.booleanLog to response proto.booleanLog to stdout.booleanCut generator for all diffs can add too many cuts for large all_diff constraints.booleanoptional double max_clause_activity_value = 18 [default = 1e+20];booleanIf a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.booleanMax number of time we perform cut generation and resolve the LP at level 0.booleanMaximum time allowed in deterministic time to solve a problem.booleanWhen loading a*x + b*y ==/!= c when x and y are both fully encoded.booleanIn the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).booleanMaximum memory allowed for the whole thread containing the solver.booleanMaximum number of conflicts allowed to solve a problem.booleanThe limit on the number of cuts in our cut pool.booleanIn case of large reduction in a presolve iteration, we perform multiple presolve iterations.booleanoptional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];booleanIf true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.booleanoptional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];booleanMaximum time allowed in seconds to solve a problem.booleanoptional double max_variable_activity_value = 16 [default = 1e+100];booleanoptional double merge_at_most_one_work_limit = 146 [default = 100000000];booleanDuring presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.booleanoptional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];booleanWhether we use a simple heuristic to try to minimize an UNSAT core.booleanA different algorithm during PB resolution.booleanoptional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];booleanParameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization.booleanIf there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread.booleanWhile adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.booleanIf true, some continuous variable might be automatically scaled.booleanAs explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.booleanEven if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.booleanTo avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.booleanWe need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.booleanAny finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.booleanAll continuous variable of the problem will be multiplied by this factor.booleanWhen scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.booleanoptional double model_reduction_log_frequency_in_seconds = 218 [default = 5];booleanhasName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.booleanAdd that many lazy constraints (or cuts) at once in the LP.booleanAfter each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.booleanoptional int32 num_search_workers = 100 [default = 0];booleanSpecify the number of parallel workers (i.e.booleanFor the cut that can be generated at any level, this control if we only try to generate them at the root node.booleanIf one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.booleanThe default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.booleanDo a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.booleanThis has no effect if optimize_with_core is false.booleanSame as for the clauses, but for the learned pseudo-Boolean constraints.booleanoptional double pb_cleanup_ratio = 47 [default = 0.5];booleanoptional bool permute_presolve_constraint_order = 179 [default = false];booleanThis is mainly here to test the solver variability.booleanIf non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.booleanWhether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.booleanoptional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];booleanWhether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.booleanApply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.booleanDuring presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.booleanDuring presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.booleanIf true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".booleanA few presolve operations involve detecting constraints included in other constraint.booleanThe maximum "deterministic" time limit to spend in probing.booleanHow much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.booleanWhether or not we use Bounded Variable Addition (BVA) in the presolve.booleanIf set at zero (the default), it is disabled.booleanSome search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.booleanThe solver ignores the pseudo costs of variables with number of recordings less than this threshold.booleanA number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.booleanRandomize fixed search.booleanThe proportion of polarity chosen at random.booleanAt the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.booleanoptional double relative_gap_limit = 160 [default = 0];booleanIf true, the solver tries to repair the solution given in the hint.booleanIn the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.booleanoptional double restart_lbd_average_ratio = 71 [default = 1];booleanRestart period for the FIXED_RESTART strategy.booleanSize of the window for the moving average restarts.booleanoptional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];booleanSearch randomization will collect equivalent 'max valued' variables, and pick one randomly.booleanAllows sharing of new learned binary clause between workers.booleanAllows sharing of the bounds of modified variables at level 0.booleanAllows objective sharing between workers.booleanSpecifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.booleanSize of the top-n different solutions kept by the solver.booleanFor an optimization problem, stop the solver as soon as we have a solution.booleanMainly used when improving the presolver.booleanThe parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.booleanAt a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.booleanWhether we try to automatically detect the symmetries in a model and exploit them.booleanHow much we try to "compress" a table constraint.booleanoptional bool use_absl_random = 180 [default = false];booleanBlock a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.booleanIf true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.booleanThis can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.booleanWhen this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.booleanWhen set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.booleanWhen this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.booleanWhether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.booleanThe solver usually exploit the LP relaxation of a model.booleanAdds a feasibility pump subsolver along with lns subsolvers.booleanIf true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.booleanStores and exploits "implied-bounds" in the solver.booleanLNS parameters.booleanFor an optimization problem, whether we follow some hints in order to find a better first solution.booleanIf true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.booleanWhen this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.booleanWhether to use pseudo-Boolean resolution to analyze a conflict.booleanIf this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().booleanWhen this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.booleanIf true, search will continuously probe Boolean variables, and integer variable bounds.booleanTurns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.booleanTurns on relaxation induced neighborhood generator.booleanoptional bool use_sat_inprocessing = 163 [default = false];booleanAdd a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.booleanWhen this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.booleanWhen this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.booleanEach time a conflict is found, the activities of some variables are increased by one.protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTablefinal booleanmergeFrom(SatParameters other) mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) mergeFrom(com.google.protobuf.Message other) final SatParameters.BuildermergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) removeSubsolverParams(int index) It is possible to specify additional subsolver configuration.setAbsoluteGapLimit(double value) Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.setAddCgCuts(boolean value) Whether we generate and add Chvatal-Gomory cuts to the LP at root node.setAddCliqueCuts(boolean value) Whether we generate clique cuts from the binary implication graph.setAddLinMaxCuts(boolean value) For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.setAddLpConstraintsLazily(boolean value) If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.setAddMirCuts(boolean value) Whether we generate MIR cuts at root node.setAddObjectiveCut(boolean value) When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.setAddZeroHalfCuts(boolean value) Whether we generate Zero-Half cuts at root node.setAlsoBumpVariablesInConflictReasons(boolean value) When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.setAutoDetectGreaterThanAtLeastOneOf(boolean value) If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];setBinarySearchNumConflicts(int value) If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.setBlockingRestartMultiplier(double value) optional double blocking_restart_multiplier = 66 [default = 1.4];setBlockingRestartWindowSize(int value) optional int32 blocking_restart_window_size = 65 [default = 5000];setBooleanEncodingLevel(int value) A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.setCatchSigintSignal(boolean value) Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.setClauseActivityDecay(double value) Clause activity parameters (same effect as the one on the variables).setClauseCleanupLbdBound(int value) All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];setClauseCleanupPeriod(int value) Trigger a cleanup when this number of "deletable" clauses is learned.optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];setClauseCleanupRatio(double value) During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.setClauseCleanupTarget(int value) During a cleanup, we will always keep that number of "deletable" clauses.setConvertIntervals(boolean value) Temporary flag util the feature is more mature.setCountAssumptionLevelsInLbd(boolean value) Whether or not the assumption levels are taken into account during the LBD computation.setCoverOptimization(boolean value) If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.setCpModelPresolve(boolean value) Whether we presolve the cp_model before solving it.setCpModelProbingLevel(int value) How much effort do we spend on probing.setCpModelUseSatPresolve(boolean value) Whether we also use the sat presolve when cp_model_presolve is true.setCutActiveCountDecay(double value) optional double cut_active_count_decay = 156 [default = 0.8];setCutCleanupTarget(int value) Target number of constraints to remove during cleanup.setCutLevel(int value) Control the global cut effort.setCutMaxActiveCountValue(double value) These parameters are similar to sat clause management activity parameters.setDebugCrashOnBadHint(boolean value) Crash if we do not manage to complete the hint into a full solution.setDebugMaxNumPresolveOperations(int value) If positive, try to stop just after that many presolve rules have been applied.setDebugPostsolveWithFullSolver(boolean value) We have two different postsolve code.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];setDefaultRestartAlgorithmsBytes(com.google.protobuf.ByteString value) optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];setDetectTableWithCost(boolean value) If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.setDisableConstraintExpansion(boolean value) If true, it disable all constraint expansion.setDiversifyLnsParams(boolean value) If true, registers more lns subsolvers with different parameters.setEnumerateAllSolutions(boolean value) Whether we enumerate all solutions of a problem without objective.setExpandAlldiffConstraints(boolean value) If true, expand all_different constraints that are not permutations.setExploitAllLpSolution(boolean value) If true and the Lp relaxation of the problem has a solution, try to exploit it.setExploitAllPrecedences(boolean value) optional bool exploit_all_precedences = 220 [default = false];setExploitBestSolution(boolean value) When branching on a variable, follow the last best solution value.setExploitIntegerLpSolution(boolean value) If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.setExploitObjective(boolean value) When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.setExploitRelaxationSolution(boolean value) When branching on a variable, follow the last best relaxation solution value.setExtraSubsolvers(int index, String value) A convenient way to add more workers types.setFillAdditionalSolutionsInResponse(boolean value) If true, the final response addition_solutions field will be filled with all solutions from our solutions pool.setFillTightenedDomainsInResponse(boolean value) If true, add information about the derived variable domains to the CpSolverResponse.setFindMultipleCores(boolean value) Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.setFixVariablesToTheirHintedValue(boolean value) If true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];setGlucoseDecayIncrement(double value) optional double glucose_decay_increment = 23 [default = 0.01];setGlucoseDecayIncrementPeriod(int value) optional int32 glucose_decay_increment_period = 24 [default = 5000];setGlucoseMaxDecay(double value) The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.setHintConflictLimit(int value) Conflict limit used in the phase that exploit the solution hint.setIgnoreNames(boolean value) If true, we don't keep names in our internal copy of the user given model.setIgnoreSubsolvers(int index, String value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];setInitialVariablesActivity(double value) The initial value of the variables activity.setInstantiateAllVariables(boolean value) If true, the solver will add a default integer branching strategy to the already defined search strategy.setInterleaveBatchSize(int value) optional int32 interleave_batch_size = 134 [default = 1];setInterleaveSearch(boolean value) Experimental.setKeepAllFeasibleSolutionsInPresolve(boolean value) If true, we disable the presolve reductions that remove feasible solutions from the search space.setLinearizationLevel(int value) A non-negative level indicating the type of constraints we consider in the LP relaxation.setLogFrequencyInSeconds(double value) Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing).setLogPrefix(String value) Add a prefix to all logs.setLogPrefixBytes(com.google.protobuf.ByteString value) Add a prefix to all logs.setLogSearchProgress(boolean value) Whether the solver should log the search progress.setLogSubsolverStatistics(boolean value) Whether the solver should display per sub-solver search statistics.setLogToResponse(boolean value) Log to response proto.setLogToStdout(boolean value) Log to stdout.setMaxAllDiffCutSize(int value) Cut generator for all diffs can add too many cuts for large all_diff constraints.setMaxClauseActivityValue(double value) optional double max_clause_activity_value = 18 [default = 1e+20];setMaxConsecutiveInactiveCount(int value) If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.setMaxCutRoundsAtLevelZero(int value) Max number of time we perform cut generation and resolve the LP at level 0.setMaxDeterministicTime(double value) Maximum time allowed in deterministic time to solve a problem.setMaxDomainSizeWhenEncodingEqNeqConstraints(int value) When loading a*x + b*y ==/!= c when x and y are both fully encoded.setMaxIntegerRoundingScaling(int value) In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).setMaxMemoryInMb(long value) Maximum memory allowed for the whole thread containing the solver.setMaxNumberOfConflicts(long value) Maximum number of conflicts allowed to solve a problem.setMaxNumCuts(int value) The limit on the number of cuts in our cut pool.setMaxPresolveIterations(int value) In case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];setMaxSatReverseAssumptionOrder(boolean value) If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];setMaxTimeInSeconds(double value) Maximum time allowed in seconds to solve a problem.setMaxVariableActivityValue(double value) optional double max_variable_activity_value = 16 [default = 1e+100];setMergeAtMostOneWorkLimit(double value) optional double merge_at_most_one_work_limit = 146 [default = 100000000];setMergeNoOverlapWorkLimit(double value) During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];setMinimizeCore(boolean value) Whether we use a simple heuristic to try to minimize an UNSAT core.setMinimizeReductionDuringPbResolution(boolean value) A different algorithm during PB resolution.setMinimizeWithPropagationNumDecisions(int value) optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];setMinimizeWithPropagationRestartPeriod(int value) Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization.setMinNumLnsWorkers(int value) If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread.setMinOrthogonalityForLpConstraints(double value) While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.setMipAutomaticallyScaleVariables(boolean value) If true, some continuous variable might be automatically scaled.setMipCheckPrecision(double value) As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.setMipComputeTrueObjectiveBound(boolean value) Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.setMipMaxActivityExponent(int value) To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.setMipMaxBound(double value) We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.setMipMaxValidMagnitude(double value) Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.setMipVarScaling(double value) All continuous variable of the problem will be multiplied by this factor.setMipWantedPrecision(double value) When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.setModelReductionLogFrequencyInSeconds(double value) optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.setNameBytes(com.google.protobuf.ByteString value) In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.setNewConstraintsBatchSize(int value) Add that many lazy constraints (or cuts) at once in the LP.setNumConflictsBeforeStrategyChanges(int value) After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.setNumSearchWorkers(int value) optional int32 num_search_workers = 100 [default = 0];setNumWorkers(int value) Specify the number of parallel workers (i.e.setOnlyAddCutsAtLevelZero(boolean value) For the cut that can be generated at any level, this control if we only try to generate them at the root node.setOnlySolveIp(boolean value) If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.setOptimizeWithCore(boolean value) The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.setOptimizeWithLbTreeSearch(boolean value) Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.setOptimizeWithMaxHs(boolean value) This has no effect if optimize_with_core is false.setPbCleanupIncrement(int value) Same as for the clauses, but for the learned pseudo-Boolean constraints.setPbCleanupRatio(double value) optional double pb_cleanup_ratio = 47 [default = 0.5];setPermutePresolveConstraintOrder(boolean value) optional bool permute_presolve_constraint_order = 179 [default = false];setPermuteVariableRandomly(boolean value) This is mainly here to test the solver variability.setPolarityRephaseIncrement(int value) If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.setPolishLpSolution(boolean value) Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];setPresolveBlockedClause(boolean value) Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.setPresolveBvaThreshold(int value) Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.setPresolveBveClauseWeight(int value) During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.setPresolveBveThreshold(int value) During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.setPresolveExtractIntegerEnforcement(boolean value) If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".setPresolveInclusionWorkLimit(long value) A few presolve operations involve detecting constraints included in other constraint.setPresolveProbingDeterministicTimeLimit(double value) The maximum "deterministic" time limit to spend in probing.setPresolveSubstitutionLevel(int value) How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.setPresolveUseBva(boolean value) Whether or not we use Bounded Variable Addition (BVA) in the presolve.setProbingPeriodAtRoot(long value) If set at zero (the default), it is disabled.setPropagationLoopDetectionFactor(double value) Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.setPseudoCostReliabilityThreshold(long value) The solver ignores the pseudo costs of variables with number of recordings less than this threshold.setRandomBranchesRatio(double value) A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.setRandomizeSearch(boolean value) Randomize fixed search.setRandomPolarityRatio(double value) The proportion of polarity chosen at random.setRandomSeed(int value) At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.setRelativeGapLimit(double value) optional double relative_gap_limit = 160 [default = 0];setRepairHint(boolean value) If true, the solver tries to repair the solution given in the hint.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) setRestartAlgorithms(int index, SatParameters.RestartAlgorithm value) The restart strategies will change each time the strategy_counter is increased.setRestartDlAverageRatio(double value) In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.setRestartLbdAverageRatio(double value) optional double restart_lbd_average_ratio = 71 [default = 1];setRestartPeriod(int value) Restart period for the FIXED_RESTART strategy.setRestartRunningWindowSize(int value) Size of the window for the moving average restarts.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];setSearchRandomizationTolerance(long value) Search randomization will collect equivalent 'max valued' variables, and pick one randomly.setShareBinaryClauses(boolean value) Allows sharing of new learned binary clause between workers.setShareLevelZeroBounds(boolean value) Allows sharing of the bounds of modified variables at level 0.setShareObjectiveBounds(boolean value) Allows objective sharing between workers.setShavingSearchDeterministicTime(double value) Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.setSolutionPoolSize(int value) Size of the top-n different solutions kept by the solver.setStopAfterFirstSolution(boolean value) For an optimization problem, stop the solver as soon as we have a solution.setStopAfterPresolve(boolean value) Mainly used when improving the presolver.setStrategyChangeIncreaseRatio(double value) The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.setSubsolverParams(int index, SatParameters value) It is possible to specify additional subsolver configuration.setSubsolverParams(int index, SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.setSubsolvers(int index, String value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.setSubsumptionDuringConflictAnalysis(boolean value) At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.setSymmetryLevel(int value) Whether we try to automatically detect the symmetries in a model and exploit them.setTableCompressionLevel(int value) How much we try to "compress" a table constraint.final SatParameters.BuildersetUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) setUseAbslRandom(boolean value) optional bool use_absl_random = 180 [default = false];setUseBlockingRestart(boolean value) Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.setUseBranchingInLp(boolean value) If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.setUseCombinedNoOverlap(boolean value) This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.setUseDisjunctiveConstraintInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.setUseDualSchedulingHeuristics(boolean value) When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.setUseEnergeticReasoningInNoOverlap2D(boolean value) When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.setUseErwaHeuristic(boolean value) Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.setUseExactLpReason(boolean value) The solver usually exploit the LP relaxation of a model.setUseFeasibilityPump(boolean value) Adds a feasibility pump subsolver along with lns subsolvers.setUseHardPrecedencesInCumulative(boolean value) If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.setUseImpliedBounds(boolean value) Stores and exploits "implied-bounds" in the solver.setUseLnsOnly(boolean value) LNS parameters.setUseOptimizationHints(boolean value) For an optimization problem, whether we follow some hints in order to find a better first solution.setUseOptionalVariables(boolean value) If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.setUseOverloadCheckerInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.setUsePbResolution(boolean value) Whether to use pseudo-Boolean resolution to analyze a conflict.setUsePhaseSaving(boolean value) If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().setUsePrecedencesInDisjunctiveConstraint(boolean value) When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.setUseProbingSearch(boolean value) If true, search will continuously probe Boolean variables, and integer variable bounds.setUseRelaxationLns(boolean value) Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.setUseRinsLns(boolean value) Turns on relaxation induced neighborhood generator.setUseSatInprocessing(boolean value) optional bool use_sat_inprocessing = 163 [default = false];setUseShavingInProbingSearch(boolean value) Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.setUseTimetableEdgeFindingInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.setUseTimetablingInNoOverlap2D(boolean value) When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.setVariableActivityDecay(double value) Each time a conflict is found, the activities of some variables are increased by one.Methods inherited from class com.google.protobuf.GeneratedMessageV3.Builder
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeFrom, newUninitializedMessageExceptionMethods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFromMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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clear
- Specified by:
clearin interfacecom.google.protobuf.Message.Builder- Specified by:
clearin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clearin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
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build
- Specified by:
buildin interfacecom.google.protobuf.Message.Builder- Specified by:
buildin interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
- Specified by:
buildPartialin interfacecom.google.protobuf.Message.Builder- Specified by:
buildPartialin interfacecom.google.protobuf.MessageLite.Builder
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clone
- Specified by:
clonein interfacecom.google.protobuf.Message.Builder- Specified by:
clonein interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clonein classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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setField
public SatParameters.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) - Specified by:
setFieldin interfacecom.google.protobuf.Message.Builder- Overrides:
setFieldin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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clearField
- Specified by:
clearFieldin interfacecom.google.protobuf.Message.Builder- Overrides:
clearFieldin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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clearOneof
- Specified by:
clearOneofin interfacecom.google.protobuf.Message.Builder- Overrides:
clearOneofin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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setRepeatedField
public SatParameters.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) - Specified by:
setRepeatedFieldin interfacecom.google.protobuf.Message.Builder- Overrides:
setRepeatedFieldin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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addRepeatedField
public SatParameters.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) - Specified by:
addRepeatedFieldin interfacecom.google.protobuf.Message.Builder- Overrides:
addRepeatedFieldin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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mergeFrom
- Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<SatParameters.Builder>
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mergeFrom
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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mergeFrom
public SatParameters.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Specified by:
mergeFromin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<SatParameters.Builder>- Throws:
IOException
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hasName
public boolean hasName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
hasNamein interfaceSatParametersOrBuilder- Returns:
- Whether the name field is set.
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getName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
getNamein interfaceSatParametersOrBuilder- Returns:
- The name.
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getNameBytes
public com.google.protobuf.ByteString getNameBytes()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
getNameBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for name.
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setName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Parameters:
value- The name to set.- Returns:
- This builder for chaining.
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clearName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Returns:
- This builder for chaining.
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setNameBytes
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Parameters:
value- The bytes for name to set.- Returns:
- This builder for chaining.
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hasPreferredVariableOrder
public boolean hasPreferredVariableOrder()optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Specified by:
hasPreferredVariableOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the preferredVariableOrder field is set.
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getPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Specified by:
getPreferredVariableOrderin interfaceSatParametersOrBuilder- Returns:
- The preferredVariableOrder.
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setPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Parameters:
value- The preferredVariableOrder to set.- Returns:
- This builder for chaining.
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clearPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Returns:
- This builder for chaining.
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hasInitialPolarity
public boolean hasInitialPolarity()optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Specified by:
hasInitialPolarityin interfaceSatParametersOrBuilder- Returns:
- Whether the initialPolarity field is set.
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getInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Specified by:
getInitialPolarityin interfaceSatParametersOrBuilder- Returns:
- The initialPolarity.
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setInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Parameters:
value- The initialPolarity to set.- Returns:
- This builder for chaining.
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clearInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Returns:
- This builder for chaining.
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hasUsePhaseSaving
public boolean hasUsePhaseSaving()If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Specified by:
hasUsePhaseSavingin interfaceSatParametersOrBuilder- Returns:
- Whether the usePhaseSaving field is set.
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getUsePhaseSaving
public boolean getUsePhaseSaving()If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Specified by:
getUsePhaseSavingin interfaceSatParametersOrBuilder- Returns:
- The usePhaseSaving.
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setUsePhaseSaving
If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Parameters:
value- The usePhaseSaving to set.- Returns:
- This builder for chaining.
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clearUsePhaseSaving
If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Returns:
- This builder for chaining.
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hasPolarityRephaseIncrement
public boolean hasPolarityRephaseIncrement()If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Specified by:
hasPolarityRephaseIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the polarityRephaseIncrement field is set.
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getPolarityRephaseIncrement
public int getPolarityRephaseIncrement()If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Specified by:
getPolarityRephaseIncrementin interfaceSatParametersOrBuilder- Returns:
- The polarityRephaseIncrement.
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setPolarityRephaseIncrement
If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Parameters:
value- The polarityRephaseIncrement to set.- Returns:
- This builder for chaining.
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clearPolarityRephaseIncrement
If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Returns:
- This builder for chaining.
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hasRandomPolarityRatio
public boolean hasRandomPolarityRatio()The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Specified by:
hasRandomPolarityRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the randomPolarityRatio field is set.
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getRandomPolarityRatio
public double getRandomPolarityRatio()The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Specified by:
getRandomPolarityRatioin interfaceSatParametersOrBuilder- Returns:
- The randomPolarityRatio.
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setRandomPolarityRatio
The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Parameters:
value- The randomPolarityRatio to set.- Returns:
- This builder for chaining.
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clearRandomPolarityRatio
The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Returns:
- This builder for chaining.
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hasRandomBranchesRatio
public boolean hasRandomBranchesRatio()A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Specified by:
hasRandomBranchesRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the randomBranchesRatio field is set.
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getRandomBranchesRatio
public double getRandomBranchesRatio()A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Specified by:
getRandomBranchesRatioin interfaceSatParametersOrBuilder- Returns:
- The randomBranchesRatio.
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setRandomBranchesRatio
A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Parameters:
value- The randomBranchesRatio to set.- Returns:
- This builder for chaining.
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clearRandomBranchesRatio
A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Returns:
- This builder for chaining.
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hasUseErwaHeuristic
public boolean hasUseErwaHeuristic()Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Specified by:
hasUseErwaHeuristicin interfaceSatParametersOrBuilder- Returns:
- Whether the useErwaHeuristic field is set.
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getUseErwaHeuristic
public boolean getUseErwaHeuristic()Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Specified by:
getUseErwaHeuristicin interfaceSatParametersOrBuilder- Returns:
- The useErwaHeuristic.
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setUseErwaHeuristic
Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Parameters:
value- The useErwaHeuristic to set.- Returns:
- This builder for chaining.
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clearUseErwaHeuristic
Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Returns:
- This builder for chaining.
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hasInitialVariablesActivity
public boolean hasInitialVariablesActivity()The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Specified by:
hasInitialVariablesActivityin interfaceSatParametersOrBuilder- Returns:
- Whether the initialVariablesActivity field is set.
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getInitialVariablesActivity
public double getInitialVariablesActivity()The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Specified by:
getInitialVariablesActivityin interfaceSatParametersOrBuilder- Returns:
- The initialVariablesActivity.
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setInitialVariablesActivity
The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Parameters:
value- The initialVariablesActivity to set.- Returns:
- This builder for chaining.
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clearInitialVariablesActivity
The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Returns:
- This builder for chaining.
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hasAlsoBumpVariablesInConflictReasons
public boolean hasAlsoBumpVariablesInConflictReasons()When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Specified by:
hasAlsoBumpVariablesInConflictReasonsin interfaceSatParametersOrBuilder- Returns:
- Whether the alsoBumpVariablesInConflictReasons field is set.
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getAlsoBumpVariablesInConflictReasons
public boolean getAlsoBumpVariablesInConflictReasons()When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Specified by:
getAlsoBumpVariablesInConflictReasonsin interfaceSatParametersOrBuilder- Returns:
- The alsoBumpVariablesInConflictReasons.
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setAlsoBumpVariablesInConflictReasons
When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Parameters:
value- The alsoBumpVariablesInConflictReasons to set.- Returns:
- This builder for chaining.
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clearAlsoBumpVariablesInConflictReasons
When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Returns:
- This builder for chaining.
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hasMinimizationAlgorithm
public boolean hasMinimizationAlgorithm()optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Specified by:
hasMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizationAlgorithm field is set.
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getMinimizationAlgorithm
optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Specified by:
getMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- The minimizationAlgorithm.
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setMinimizationAlgorithm
public SatParameters.Builder setMinimizationAlgorithm(SatParameters.ConflictMinimizationAlgorithm value) optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Parameters:
value- The minimizationAlgorithm to set.- Returns:
- This builder for chaining.
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clearMinimizationAlgorithm
optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Returns:
- This builder for chaining.
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hasBinaryMinimizationAlgorithm
public boolean hasBinaryMinimizationAlgorithm()optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];- Specified by:
hasBinaryMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- Whether the binaryMinimizationAlgorithm field is set.
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getBinaryMinimizationAlgorithm
optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];- Specified by:
getBinaryMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- The binaryMinimizationAlgorithm.
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setBinaryMinimizationAlgorithm
public SatParameters.Builder setBinaryMinimizationAlgorithm(SatParameters.BinaryMinizationAlgorithm value) optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];- Parameters:
value- The binaryMinimizationAlgorithm to set.- Returns:
- This builder for chaining.
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clearBinaryMinimizationAlgorithm
optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FIRST];- Returns:
- This builder for chaining.
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hasSubsumptionDuringConflictAnalysis
public boolean hasSubsumptionDuringConflictAnalysis()At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Specified by:
hasSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- Whether the subsumptionDuringConflictAnalysis field is set.
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getSubsumptionDuringConflictAnalysis
public boolean getSubsumptionDuringConflictAnalysis()At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Specified by:
getSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- The subsumptionDuringConflictAnalysis.
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setSubsumptionDuringConflictAnalysis
At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Parameters:
value- The subsumptionDuringConflictAnalysis to set.- Returns:
- This builder for chaining.
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clearSubsumptionDuringConflictAnalysis
At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Returns:
- This builder for chaining.
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hasClauseCleanupPeriod
public boolean hasClauseCleanupPeriod()Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Specified by:
hasClauseCleanupPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupPeriod field is set.
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getClauseCleanupPeriod
public int getClauseCleanupPeriod()Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Specified by:
getClauseCleanupPeriodin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupPeriod.
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setClauseCleanupPeriod
Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Parameters:
value- The clauseCleanupPeriod to set.- Returns:
- This builder for chaining.
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clearClauseCleanupPeriod
Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Returns:
- This builder for chaining.
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hasClauseCleanupTarget
public boolean hasClauseCleanupTarget()During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Specified by:
hasClauseCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupTarget field is set.
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getClauseCleanupTarget
public int getClauseCleanupTarget()During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Specified by:
getClauseCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupTarget.
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setClauseCleanupTarget
During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Parameters:
value- The clauseCleanupTarget to set.- Returns:
- This builder for chaining.
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clearClauseCleanupTarget
During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Returns:
- This builder for chaining.
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hasClauseCleanupRatio
public boolean hasClauseCleanupRatio()During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Specified by:
hasClauseCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupRatio field is set.
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getClauseCleanupRatio
public double getClauseCleanupRatio()During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Specified by:
getClauseCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupRatio.
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setClauseCleanupRatio
During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Parameters:
value- The clauseCleanupRatio to set.- Returns:
- This builder for chaining.
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clearClauseCleanupRatio
During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Returns:
- This builder for chaining.
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hasClauseCleanupProtection
public boolean hasClauseCleanupProtection()optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];- Specified by:
hasClauseCleanupProtectionin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupProtection field is set.
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getClauseCleanupProtection
optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];- Specified by:
getClauseCleanupProtectionin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupProtection.
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setClauseCleanupProtection
optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];- Parameters:
value- The clauseCleanupProtection to set.- Returns:
- This builder for chaining.
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clearClauseCleanupProtection
optional .operations_research.sat.SatParameters.ClauseProtection clause_cleanup_protection = 58 [default = PROTECTION_NONE];- Returns:
- This builder for chaining.
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hasClauseCleanupLbdBound
public boolean hasClauseCleanupLbdBound()All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Specified by:
hasClauseCleanupLbdBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupLbdBound field is set.
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getClauseCleanupLbdBound
public int getClauseCleanupLbdBound()All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Specified by:
getClauseCleanupLbdBoundin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupLbdBound.
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setClauseCleanupLbdBound
All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Parameters:
value- The clauseCleanupLbdBound to set.- Returns:
- This builder for chaining.
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clearClauseCleanupLbdBound
All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Returns:
- This builder for chaining.
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hasClauseCleanupOrdering
public boolean hasClauseCleanupOrdering()optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Specified by:
hasClauseCleanupOrderingin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupOrdering field is set.
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getClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Specified by:
getClauseCleanupOrderingin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupOrdering.
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setClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Parameters:
value- The clauseCleanupOrdering to set.- Returns:
- This builder for chaining.
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clearClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Returns:
- This builder for chaining.
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hasPbCleanupIncrement
public boolean hasPbCleanupIncrement()Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Specified by:
hasPbCleanupIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the pbCleanupIncrement field is set.
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getPbCleanupIncrement
public int getPbCleanupIncrement()Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Specified by:
getPbCleanupIncrementin interfaceSatParametersOrBuilder- Returns:
- The pbCleanupIncrement.
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setPbCleanupIncrement
Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Parameters:
value- The pbCleanupIncrement to set.- Returns:
- This builder for chaining.
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clearPbCleanupIncrement
Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Returns:
- This builder for chaining.
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hasPbCleanupRatio
public boolean hasPbCleanupRatio()optional double pb_cleanup_ratio = 47 [default = 0.5];- Specified by:
hasPbCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the pbCleanupRatio field is set.
-
getPbCleanupRatio
public double getPbCleanupRatio()optional double pb_cleanup_ratio = 47 [default = 0.5];- Specified by:
getPbCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- The pbCleanupRatio.
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setPbCleanupRatio
optional double pb_cleanup_ratio = 47 [default = 0.5];- Parameters:
value- The pbCleanupRatio to set.- Returns:
- This builder for chaining.
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clearPbCleanupRatio
optional double pb_cleanup_ratio = 47 [default = 0.5];- Returns:
- This builder for chaining.
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hasMinimizeWithPropagationRestartPeriod
public boolean hasMinimizeWithPropagationRestartPeriod()Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper. Changing these parameters or the kind of clause we minimize seems to have a big impact on the overall perf on our benchmarks. So this technique seems definitely useful, but it is hard to tune properly.
optional int32 minimize_with_propagation_restart_period = 96 [default = 10];- Specified by:
hasMinimizeWithPropagationRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizeWithPropagationRestartPeriod field is set.
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getMinimizeWithPropagationRestartPeriod
public int getMinimizeWithPropagationRestartPeriod()Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper. Changing these parameters or the kind of clause we minimize seems to have a big impact on the overall perf on our benchmarks. So this technique seems definitely useful, but it is hard to tune properly.
optional int32 minimize_with_propagation_restart_period = 96 [default = 10];- Specified by:
getMinimizeWithPropagationRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- The minimizeWithPropagationRestartPeriod.
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setMinimizeWithPropagationRestartPeriod
Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper. Changing these parameters or the kind of clause we minimize seems to have a big impact on the overall perf on our benchmarks. So this technique seems definitely useful, but it is hard to tune properly.
optional int32 minimize_with_propagation_restart_period = 96 [default = 10];- Parameters:
value- The minimizeWithPropagationRestartPeriod to set.- Returns:
- This builder for chaining.
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clearMinimizeWithPropagationRestartPeriod
Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf For now, we have a somewhat simpler implementation where every x restart we spend y decisions on clause minimization. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper. Changing these parameters or the kind of clause we minimize seems to have a big impact on the overall perf on our benchmarks. So this technique seems definitely useful, but it is hard to tune properly.
optional int32 minimize_with_propagation_restart_period = 96 [default = 10];- Returns:
- This builder for chaining.
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hasMinimizeWithPropagationNumDecisions
public boolean hasMinimizeWithPropagationNumDecisions()optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];- Specified by:
hasMinimizeWithPropagationNumDecisionsin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizeWithPropagationNumDecisions field is set.
-
getMinimizeWithPropagationNumDecisions
public int getMinimizeWithPropagationNumDecisions()optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];- Specified by:
getMinimizeWithPropagationNumDecisionsin interfaceSatParametersOrBuilder- Returns:
- The minimizeWithPropagationNumDecisions.
-
setMinimizeWithPropagationNumDecisions
optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];- Parameters:
value- The minimizeWithPropagationNumDecisions to set.- Returns:
- This builder for chaining.
-
clearMinimizeWithPropagationNumDecisions
optional int32 minimize_with_propagation_num_decisions = 97 [default = 1000];- Returns:
- This builder for chaining.
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hasVariableActivityDecay
public boolean hasVariableActivityDecay()Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Specified by:
hasVariableActivityDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the variableActivityDecay field is set.
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getVariableActivityDecay
public double getVariableActivityDecay()Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Specified by:
getVariableActivityDecayin interfaceSatParametersOrBuilder- Returns:
- The variableActivityDecay.
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setVariableActivityDecay
Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Parameters:
value- The variableActivityDecay to set.- Returns:
- This builder for chaining.
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clearVariableActivityDecay
Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Returns:
- This builder for chaining.
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hasMaxVariableActivityValue
public boolean hasMaxVariableActivityValue()optional double max_variable_activity_value = 16 [default = 1e+100];- Specified by:
hasMaxVariableActivityValuein interfaceSatParametersOrBuilder- Returns:
- Whether the maxVariableActivityValue field is set.
-
getMaxVariableActivityValue
public double getMaxVariableActivityValue()optional double max_variable_activity_value = 16 [default = 1e+100];- Specified by:
getMaxVariableActivityValuein interfaceSatParametersOrBuilder- Returns:
- The maxVariableActivityValue.
-
setMaxVariableActivityValue
optional double max_variable_activity_value = 16 [default = 1e+100];- Parameters:
value- The maxVariableActivityValue to set.- Returns:
- This builder for chaining.
-
clearMaxVariableActivityValue
optional double max_variable_activity_value = 16 [default = 1e+100];- Returns:
- This builder for chaining.
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hasGlucoseMaxDecay
public boolean hasGlucoseMaxDecay()The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Specified by:
hasGlucoseMaxDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseMaxDecay field is set.
-
getGlucoseMaxDecay
public double getGlucoseMaxDecay()The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Specified by:
getGlucoseMaxDecayin interfaceSatParametersOrBuilder- Returns:
- The glucoseMaxDecay.
-
setGlucoseMaxDecay
The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Parameters:
value- The glucoseMaxDecay to set.- Returns:
- This builder for chaining.
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clearGlucoseMaxDecay
The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Returns:
- This builder for chaining.
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hasGlucoseDecayIncrement
public boolean hasGlucoseDecayIncrement()optional double glucose_decay_increment = 23 [default = 0.01];- Specified by:
hasGlucoseDecayIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseDecayIncrement field is set.
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getGlucoseDecayIncrement
public double getGlucoseDecayIncrement()optional double glucose_decay_increment = 23 [default = 0.01];- Specified by:
getGlucoseDecayIncrementin interfaceSatParametersOrBuilder- Returns:
- The glucoseDecayIncrement.
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setGlucoseDecayIncrement
optional double glucose_decay_increment = 23 [default = 0.01];- Parameters:
value- The glucoseDecayIncrement to set.- Returns:
- This builder for chaining.
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clearGlucoseDecayIncrement
optional double glucose_decay_increment = 23 [default = 0.01];- Returns:
- This builder for chaining.
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hasGlucoseDecayIncrementPeriod
public boolean hasGlucoseDecayIncrementPeriod()optional int32 glucose_decay_increment_period = 24 [default = 5000];- Specified by:
hasGlucoseDecayIncrementPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseDecayIncrementPeriod field is set.
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getGlucoseDecayIncrementPeriod
public int getGlucoseDecayIncrementPeriod()optional int32 glucose_decay_increment_period = 24 [default = 5000];- Specified by:
getGlucoseDecayIncrementPeriodin interfaceSatParametersOrBuilder- Returns:
- The glucoseDecayIncrementPeriod.
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setGlucoseDecayIncrementPeriod
optional int32 glucose_decay_increment_period = 24 [default = 5000];- Parameters:
value- The glucoseDecayIncrementPeriod to set.- Returns:
- This builder for chaining.
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clearGlucoseDecayIncrementPeriod
optional int32 glucose_decay_increment_period = 24 [default = 5000];- Returns:
- This builder for chaining.
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hasClauseActivityDecay
public boolean hasClauseActivityDecay()Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Specified by:
hasClauseActivityDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseActivityDecay field is set.
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getClauseActivityDecay
public double getClauseActivityDecay()Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Specified by:
getClauseActivityDecayin interfaceSatParametersOrBuilder- Returns:
- The clauseActivityDecay.
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setClauseActivityDecay
Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Parameters:
value- The clauseActivityDecay to set.- Returns:
- This builder for chaining.
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clearClauseActivityDecay
Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Returns:
- This builder for chaining.
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hasMaxClauseActivityValue
public boolean hasMaxClauseActivityValue()optional double max_clause_activity_value = 18 [default = 1e+20];- Specified by:
hasMaxClauseActivityValuein interfaceSatParametersOrBuilder- Returns:
- Whether the maxClauseActivityValue field is set.
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getMaxClauseActivityValue
public double getMaxClauseActivityValue()optional double max_clause_activity_value = 18 [default = 1e+20];- Specified by:
getMaxClauseActivityValuein interfaceSatParametersOrBuilder- Returns:
- The maxClauseActivityValue.
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setMaxClauseActivityValue
optional double max_clause_activity_value = 18 [default = 1e+20];- Parameters:
value- The maxClauseActivityValue to set.- Returns:
- This builder for chaining.
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clearMaxClauseActivityValue
optional double max_clause_activity_value = 18 [default = 1e+20];- Returns:
- This builder for chaining.
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getRestartAlgorithmsList
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsListin interfaceSatParametersOrBuilder- Returns:
- A list containing the restartAlgorithms.
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getRestartAlgorithmsCount
public int getRestartAlgorithmsCount()The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsCountin interfaceSatParametersOrBuilder- Returns:
- The count of restartAlgorithms.
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getRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The restartAlgorithms at the given index.
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setRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
index- The index to set the value at.value- The restartAlgorithms to set.- Returns:
- This builder for chaining.
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addRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
value- The restartAlgorithms to add.- Returns:
- This builder for chaining.
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addAllRestartAlgorithms
public SatParameters.Builder addAllRestartAlgorithms(Iterable<? extends SatParameters.RestartAlgorithm> values) The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
values- The restartAlgorithms to add.- Returns:
- This builder for chaining.
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clearRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Returns:
- This builder for chaining.
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hasDefaultRestartAlgorithms
public boolean hasDefaultRestartAlgorithms()optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
hasDefaultRestartAlgorithmsin interfaceSatParametersOrBuilder- Returns:
- Whether the defaultRestartAlgorithms field is set.
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getDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
getDefaultRestartAlgorithmsin interfaceSatParametersOrBuilder- Returns:
- The defaultRestartAlgorithms.
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getDefaultRestartAlgorithmsBytes
public com.google.protobuf.ByteString getDefaultRestartAlgorithmsBytes()optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
getDefaultRestartAlgorithmsBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for defaultRestartAlgorithms.
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setDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Parameters:
value- The defaultRestartAlgorithms to set.- Returns:
- This builder for chaining.
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clearDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Returns:
- This builder for chaining.
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setDefaultRestartAlgorithmsBytes
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Parameters:
value- The bytes for defaultRestartAlgorithms to set.- Returns:
- This builder for chaining.
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hasRestartPeriod
public boolean hasRestartPeriod()Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Specified by:
hasRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the restartPeriod field is set.
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getRestartPeriod
public int getRestartPeriod()Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Specified by:
getRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- The restartPeriod.
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setRestartPeriod
Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Parameters:
value- The restartPeriod to set.- Returns:
- This builder for chaining.
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clearRestartPeriod
Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Returns:
- This builder for chaining.
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hasRestartRunningWindowSize
public boolean hasRestartRunningWindowSize()Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Specified by:
hasRestartRunningWindowSizein interfaceSatParametersOrBuilder- Returns:
- Whether the restartRunningWindowSize field is set.
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getRestartRunningWindowSize
public int getRestartRunningWindowSize()Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Specified by:
getRestartRunningWindowSizein interfaceSatParametersOrBuilder- Returns:
- The restartRunningWindowSize.
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setRestartRunningWindowSize
Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Parameters:
value- The restartRunningWindowSize to set.- Returns:
- This builder for chaining.
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clearRestartRunningWindowSize
Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Returns:
- This builder for chaining.
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hasRestartDlAverageRatio
public boolean hasRestartDlAverageRatio()In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Specified by:
hasRestartDlAverageRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the restartDlAverageRatio field is set.
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getRestartDlAverageRatio
public double getRestartDlAverageRatio()In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Specified by:
getRestartDlAverageRatioin interfaceSatParametersOrBuilder- Returns:
- The restartDlAverageRatio.
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setRestartDlAverageRatio
In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Parameters:
value- The restartDlAverageRatio to set.- Returns:
- This builder for chaining.
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clearRestartDlAverageRatio
In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Returns:
- This builder for chaining.
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hasRestartLbdAverageRatio
public boolean hasRestartLbdAverageRatio()optional double restart_lbd_average_ratio = 71 [default = 1];- Specified by:
hasRestartLbdAverageRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the restartLbdAverageRatio field is set.
-
getRestartLbdAverageRatio
public double getRestartLbdAverageRatio()optional double restart_lbd_average_ratio = 71 [default = 1];- Specified by:
getRestartLbdAverageRatioin interfaceSatParametersOrBuilder- Returns:
- The restartLbdAverageRatio.
-
setRestartLbdAverageRatio
optional double restart_lbd_average_ratio = 71 [default = 1];- Parameters:
value- The restartLbdAverageRatio to set.- Returns:
- This builder for chaining.
-
clearRestartLbdAverageRatio
optional double restart_lbd_average_ratio = 71 [default = 1];- Returns:
- This builder for chaining.
-
hasUseBlockingRestart
public boolean hasUseBlockingRestart()Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Specified by:
hasUseBlockingRestartin interfaceSatParametersOrBuilder- Returns:
- Whether the useBlockingRestart field is set.
-
getUseBlockingRestart
public boolean getUseBlockingRestart()Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Specified by:
getUseBlockingRestartin interfaceSatParametersOrBuilder- Returns:
- The useBlockingRestart.
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setUseBlockingRestart
Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Parameters:
value- The useBlockingRestart to set.- Returns:
- This builder for chaining.
-
clearUseBlockingRestart
Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Returns:
- This builder for chaining.
-
hasBlockingRestartWindowSize
public boolean hasBlockingRestartWindowSize()optional int32 blocking_restart_window_size = 65 [default = 5000];- Specified by:
hasBlockingRestartWindowSizein interfaceSatParametersOrBuilder- Returns:
- Whether the blockingRestartWindowSize field is set.
-
getBlockingRestartWindowSize
public int getBlockingRestartWindowSize()optional int32 blocking_restart_window_size = 65 [default = 5000];- Specified by:
getBlockingRestartWindowSizein interfaceSatParametersOrBuilder- Returns:
- The blockingRestartWindowSize.
-
setBlockingRestartWindowSize
optional int32 blocking_restart_window_size = 65 [default = 5000];- Parameters:
value- The blockingRestartWindowSize to set.- Returns:
- This builder for chaining.
-
clearBlockingRestartWindowSize
optional int32 blocking_restart_window_size = 65 [default = 5000];- Returns:
- This builder for chaining.
-
hasBlockingRestartMultiplier
public boolean hasBlockingRestartMultiplier()optional double blocking_restart_multiplier = 66 [default = 1.4];- Specified by:
hasBlockingRestartMultiplierin interfaceSatParametersOrBuilder- Returns:
- Whether the blockingRestartMultiplier field is set.
-
getBlockingRestartMultiplier
public double getBlockingRestartMultiplier()optional double blocking_restart_multiplier = 66 [default = 1.4];- Specified by:
getBlockingRestartMultiplierin interfaceSatParametersOrBuilder- Returns:
- The blockingRestartMultiplier.
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setBlockingRestartMultiplier
optional double blocking_restart_multiplier = 66 [default = 1.4];- Parameters:
value- The blockingRestartMultiplier to set.- Returns:
- This builder for chaining.
-
clearBlockingRestartMultiplier
optional double blocking_restart_multiplier = 66 [default = 1.4];- Returns:
- This builder for chaining.
-
hasNumConflictsBeforeStrategyChanges
public boolean hasNumConflictsBeforeStrategyChanges()After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Specified by:
hasNumConflictsBeforeStrategyChangesin interfaceSatParametersOrBuilder- Returns:
- Whether the numConflictsBeforeStrategyChanges field is set.
-
getNumConflictsBeforeStrategyChanges
public int getNumConflictsBeforeStrategyChanges()After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Specified by:
getNumConflictsBeforeStrategyChangesin interfaceSatParametersOrBuilder- Returns:
- The numConflictsBeforeStrategyChanges.
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setNumConflictsBeforeStrategyChanges
After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Parameters:
value- The numConflictsBeforeStrategyChanges to set.- Returns:
- This builder for chaining.
-
clearNumConflictsBeforeStrategyChanges
After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Returns:
- This builder for chaining.
-
hasStrategyChangeIncreaseRatio
public boolean hasStrategyChangeIncreaseRatio()The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Specified by:
hasStrategyChangeIncreaseRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the strategyChangeIncreaseRatio field is set.
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getStrategyChangeIncreaseRatio
public double getStrategyChangeIncreaseRatio()The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Specified by:
getStrategyChangeIncreaseRatioin interfaceSatParametersOrBuilder- Returns:
- The strategyChangeIncreaseRatio.
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setStrategyChangeIncreaseRatio
The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Parameters:
value- The strategyChangeIncreaseRatio to set.- Returns:
- This builder for chaining.
-
clearStrategyChangeIncreaseRatio
The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Returns:
- This builder for chaining.
-
hasMaxTimeInSeconds
public boolean hasMaxTimeInSeconds()Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Specified by:
hasMaxTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxTimeInSeconds field is set.
-
getMaxTimeInSeconds
public double getMaxTimeInSeconds()Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Specified by:
getMaxTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- The maxTimeInSeconds.
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setMaxTimeInSeconds
Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Parameters:
value- The maxTimeInSeconds to set.- Returns:
- This builder for chaining.
-
clearMaxTimeInSeconds
Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Returns:
- This builder for chaining.
-
hasMaxDeterministicTime
public boolean hasMaxDeterministicTime()Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Specified by:
hasMaxDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- Whether the maxDeterministicTime field is set.
-
getMaxDeterministicTime
public double getMaxDeterministicTime()Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Specified by:
getMaxDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- The maxDeterministicTime.
-
setMaxDeterministicTime
Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Parameters:
value- The maxDeterministicTime to set.- Returns:
- This builder for chaining.
-
clearMaxDeterministicTime
Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Returns:
- This builder for chaining.
-
hasMaxNumberOfConflicts
public boolean hasMaxNumberOfConflicts()Maximum number of conflicts allowed to solve a problem. TODO(user,user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Specified by:
hasMaxNumberOfConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumberOfConflicts field is set.
-
getMaxNumberOfConflicts
public long getMaxNumberOfConflicts()Maximum number of conflicts allowed to solve a problem. TODO(user,user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Specified by:
getMaxNumberOfConflictsin interfaceSatParametersOrBuilder- Returns:
- The maxNumberOfConflicts.
-
setMaxNumberOfConflicts
Maximum number of conflicts allowed to solve a problem. TODO(user,user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Parameters:
value- The maxNumberOfConflicts to set.- Returns:
- This builder for chaining.
-
clearMaxNumberOfConflicts
Maximum number of conflicts allowed to solve a problem. TODO(user,user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Returns:
- This builder for chaining.
-
hasMaxMemoryInMb
public boolean hasMaxMemoryInMb()Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Specified by:
hasMaxMemoryInMbin interfaceSatParametersOrBuilder- Returns:
- Whether the maxMemoryInMb field is set.
-
getMaxMemoryInMb
public long getMaxMemoryInMb()Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Specified by:
getMaxMemoryInMbin interfaceSatParametersOrBuilder- Returns:
- The maxMemoryInMb.
-
setMaxMemoryInMb
Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Parameters:
value- The maxMemoryInMb to set.- Returns:
- This builder for chaining.
-
clearMaxMemoryInMb
Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Returns:
- This builder for chaining.
-
hasAbsoluteGapLimit
public boolean hasAbsoluteGapLimit()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Specified by:
hasAbsoluteGapLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the absoluteGapLimit field is set.
-
getAbsoluteGapLimit
public double getAbsoluteGapLimit()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Specified by:
getAbsoluteGapLimitin interfaceSatParametersOrBuilder- Returns:
- The absoluteGapLimit.
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setAbsoluteGapLimit
Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Parameters:
value- The absoluteGapLimit to set.- Returns:
- This builder for chaining.
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clearAbsoluteGapLimit
Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Returns:
- This builder for chaining.
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hasRelativeGapLimit
public boolean hasRelativeGapLimit()optional double relative_gap_limit = 160 [default = 0];- Specified by:
hasRelativeGapLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the relativeGapLimit field is set.
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getRelativeGapLimit
public double getRelativeGapLimit()optional double relative_gap_limit = 160 [default = 0];- Specified by:
getRelativeGapLimitin interfaceSatParametersOrBuilder- Returns:
- The relativeGapLimit.
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setRelativeGapLimit
optional double relative_gap_limit = 160 [default = 0];- Parameters:
value- The relativeGapLimit to set.- Returns:
- This builder for chaining.
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clearRelativeGapLimit
optional double relative_gap_limit = 160 [default = 0];- Returns:
- This builder for chaining.
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hasRandomSeed
public boolean hasRandomSeed()At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Specified by:
hasRandomSeedin interfaceSatParametersOrBuilder- Returns:
- Whether the randomSeed field is set.
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getRandomSeed
public int getRandomSeed()At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Specified by:
getRandomSeedin interfaceSatParametersOrBuilder- Returns:
- The randomSeed.
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setRandomSeed
At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Parameters:
value- The randomSeed to set.- Returns:
- This builder for chaining.
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clearRandomSeed
At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Returns:
- This builder for chaining.
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hasPermuteVariableRandomly
public boolean hasPermuteVariableRandomly()This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Specified by:
hasPermuteVariableRandomlyin interfaceSatParametersOrBuilder- Returns:
- Whether the permuteVariableRandomly field is set.
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getPermuteVariableRandomly
public boolean getPermuteVariableRandomly()This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Specified by:
getPermuteVariableRandomlyin interfaceSatParametersOrBuilder- Returns:
- The permuteVariableRandomly.
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setPermuteVariableRandomly
This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Parameters:
value- The permuteVariableRandomly to set.- Returns:
- This builder for chaining.
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clearPermuteVariableRandomly
This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Returns:
- This builder for chaining.
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hasPermutePresolveConstraintOrder
public boolean hasPermutePresolveConstraintOrder()optional bool permute_presolve_constraint_order = 179 [default = false];- Specified by:
hasPermutePresolveConstraintOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the permutePresolveConstraintOrder field is set.
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getPermutePresolveConstraintOrder
public boolean getPermutePresolveConstraintOrder()optional bool permute_presolve_constraint_order = 179 [default = false];- Specified by:
getPermutePresolveConstraintOrderin interfaceSatParametersOrBuilder- Returns:
- The permutePresolveConstraintOrder.
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setPermutePresolveConstraintOrder
optional bool permute_presolve_constraint_order = 179 [default = false];- Parameters:
value- The permutePresolveConstraintOrder to set.- Returns:
- This builder for chaining.
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clearPermutePresolveConstraintOrder
optional bool permute_presolve_constraint_order = 179 [default = false];- Returns:
- This builder for chaining.
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hasUseAbslRandom
public boolean hasUseAbslRandom()optional bool use_absl_random = 180 [default = false];- Specified by:
hasUseAbslRandomin interfaceSatParametersOrBuilder- Returns:
- Whether the useAbslRandom field is set.
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getUseAbslRandom
public boolean getUseAbslRandom()optional bool use_absl_random = 180 [default = false];- Specified by:
getUseAbslRandomin interfaceSatParametersOrBuilder- Returns:
- The useAbslRandom.
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setUseAbslRandom
optional bool use_absl_random = 180 [default = false];- Parameters:
value- The useAbslRandom to set.- Returns:
- This builder for chaining.
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clearUseAbslRandom
optional bool use_absl_random = 180 [default = false];- Returns:
- This builder for chaining.
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hasLogSearchProgress
public boolean hasLogSearchProgress()Whether the solver should log the search progress. By default, it logs to LOG(INFO). This can be overwritten by the log_destination parameter.
optional bool log_search_progress = 41 [default = false];- Specified by:
hasLogSearchProgressin interfaceSatParametersOrBuilder- Returns:
- Whether the logSearchProgress field is set.
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getLogSearchProgress
public boolean getLogSearchProgress()Whether the solver should log the search progress. By default, it logs to LOG(INFO). This can be overwritten by the log_destination parameter.
optional bool log_search_progress = 41 [default = false];- Specified by:
getLogSearchProgressin interfaceSatParametersOrBuilder- Returns:
- The logSearchProgress.
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setLogSearchProgress
Whether the solver should log the search progress. By default, it logs to LOG(INFO). This can be overwritten by the log_destination parameter.
optional bool log_search_progress = 41 [default = false];- Parameters:
value- The logSearchProgress to set.- Returns:
- This builder for chaining.
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clearLogSearchProgress
Whether the solver should log the search progress. By default, it logs to LOG(INFO). This can be overwritten by the log_destination parameter.
optional bool log_search_progress = 41 [default = false];- Returns:
- This builder for chaining.
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hasLogFrequencyInSeconds
public boolean hasLogFrequencyInSeconds()Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing). A value < 0 will disable periodic logs.
optional double log_frequency_in_seconds = 212 [default = -1];- Specified by:
hasLogFrequencyInSecondsin interfaceSatParametersOrBuilder- Returns:
- Whether the logFrequencyInSeconds field is set.
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getLogFrequencyInSeconds
public double getLogFrequencyInSeconds()Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing). A value < 0 will disable periodic logs.
optional double log_frequency_in_seconds = 212 [default = -1];- Specified by:
getLogFrequencyInSecondsin interfaceSatParametersOrBuilder- Returns:
- The logFrequencyInSeconds.
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setLogFrequencyInSeconds
Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing). A value < 0 will disable periodic logs.
optional double log_frequency_in_seconds = 212 [default = -1];- Parameters:
value- The logFrequencyInSeconds to set.- Returns:
- This builder for chaining.
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clearLogFrequencyInSeconds
Indicates how much logging should wait before logging periodic search information from specialized workers (lb_tree_search, probing). A value < 0 will disable periodic logs.
optional double log_frequency_in_seconds = 212 [default = -1];- Returns:
- This builder for chaining.
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hasModelReductionLogFrequencyInSeconds
public boolean hasModelReductionLogFrequencyInSeconds()optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];- Specified by:
hasModelReductionLogFrequencyInSecondsin interfaceSatParametersOrBuilder- Returns:
- Whether the modelReductionLogFrequencyInSeconds field is set.
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getModelReductionLogFrequencyInSeconds
public double getModelReductionLogFrequencyInSeconds()optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];- Specified by:
getModelReductionLogFrequencyInSecondsin interfaceSatParametersOrBuilder- Returns:
- The modelReductionLogFrequencyInSeconds.
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setModelReductionLogFrequencyInSeconds
optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];- Parameters:
value- The modelReductionLogFrequencyInSeconds to set.- Returns:
- This builder for chaining.
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clearModelReductionLogFrequencyInSeconds
optional double model_reduction_log_frequency_in_seconds = 218 [default = 5];- Returns:
- This builder for chaining.
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hasLogSubsolverStatistics
public boolean hasLogSubsolverStatistics()Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1.
optional bool log_subsolver_statistics = 189 [default = true];- Specified by:
hasLogSubsolverStatisticsin interfaceSatParametersOrBuilder- Returns:
- Whether the logSubsolverStatistics field is set.
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getLogSubsolverStatistics
public boolean getLogSubsolverStatistics()Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1.
optional bool log_subsolver_statistics = 189 [default = true];- Specified by:
getLogSubsolverStatisticsin interfaceSatParametersOrBuilder- Returns:
- The logSubsolverStatistics.
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setLogSubsolverStatistics
Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1.
optional bool log_subsolver_statistics = 189 [default = true];- Parameters:
value- The logSubsolverStatistics to set.- Returns:
- This builder for chaining.
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clearLogSubsolverStatistics
Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1.
optional bool log_subsolver_statistics = 189 [default = true];- Returns:
- This builder for chaining.
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hasLogPrefix
public boolean hasLogPrefix()Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
hasLogPrefixin interfaceSatParametersOrBuilder- Returns:
- Whether the logPrefix field is set.
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getLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
getLogPrefixin interfaceSatParametersOrBuilder- Returns:
- The logPrefix.
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getLogPrefixBytes
public com.google.protobuf.ByteString getLogPrefixBytes()Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
getLogPrefixBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for logPrefix.
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setLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Parameters:
value- The logPrefix to set.- Returns:
- This builder for chaining.
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clearLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Returns:
- This builder for chaining.
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setLogPrefixBytes
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Parameters:
value- The bytes for logPrefix to set.- Returns:
- This builder for chaining.
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hasLogToStdout
public boolean hasLogToStdout()Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Specified by:
hasLogToStdoutin interfaceSatParametersOrBuilder- Returns:
- Whether the logToStdout field is set.
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getLogToStdout
public boolean getLogToStdout()Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Specified by:
getLogToStdoutin interfaceSatParametersOrBuilder- Returns:
- The logToStdout.
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setLogToStdout
Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Parameters:
value- The logToStdout to set.- Returns:
- This builder for chaining.
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clearLogToStdout
Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Returns:
- This builder for chaining.
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hasLogToResponse
public boolean hasLogToResponse()Log to response proto.
optional bool log_to_response = 187 [default = false];- Specified by:
hasLogToResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the logToResponse field is set.
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getLogToResponse
public boolean getLogToResponse()Log to response proto.
optional bool log_to_response = 187 [default = false];- Specified by:
getLogToResponsein interfaceSatParametersOrBuilder- Returns:
- The logToResponse.
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setLogToResponse
Log to response proto.
optional bool log_to_response = 187 [default = false];- Parameters:
value- The logToResponse to set.- Returns:
- This builder for chaining.
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clearLogToResponse
Log to response proto.
optional bool log_to_response = 187 [default = false];- Returns:
- This builder for chaining.
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hasUsePbResolution
public boolean hasUsePbResolution()Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Specified by:
hasUsePbResolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the usePbResolution field is set.
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getUsePbResolution
public boolean getUsePbResolution()Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Specified by:
getUsePbResolutionin interfaceSatParametersOrBuilder- Returns:
- The usePbResolution.
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setUsePbResolution
Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Parameters:
value- The usePbResolution to set.- Returns:
- This builder for chaining.
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clearUsePbResolution
Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Returns:
- This builder for chaining.
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hasMinimizeReductionDuringPbResolution
public boolean hasMinimizeReductionDuringPbResolution()A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Specified by:
hasMinimizeReductionDuringPbResolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizeReductionDuringPbResolution field is set.
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getMinimizeReductionDuringPbResolution
public boolean getMinimizeReductionDuringPbResolution()A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Specified by:
getMinimizeReductionDuringPbResolutionin interfaceSatParametersOrBuilder- Returns:
- The minimizeReductionDuringPbResolution.
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setMinimizeReductionDuringPbResolution
A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Parameters:
value- The minimizeReductionDuringPbResolution to set.- Returns:
- This builder for chaining.
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clearMinimizeReductionDuringPbResolution
A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Returns:
- This builder for chaining.
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hasCountAssumptionLevelsInLbd
public boolean hasCountAssumptionLevelsInLbd()Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Specified by:
hasCountAssumptionLevelsInLbdin interfaceSatParametersOrBuilder- Returns:
- Whether the countAssumptionLevelsInLbd field is set.
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getCountAssumptionLevelsInLbd
public boolean getCountAssumptionLevelsInLbd()Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Specified by:
getCountAssumptionLevelsInLbdin interfaceSatParametersOrBuilder- Returns:
- The countAssumptionLevelsInLbd.
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setCountAssumptionLevelsInLbd
Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Parameters:
value- The countAssumptionLevelsInLbd to set.- Returns:
- This builder for chaining.
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clearCountAssumptionLevelsInLbd
Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Returns:
- This builder for chaining.
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hasPresolveBveThreshold
public boolean hasPresolveBveThreshold()During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Specified by:
hasPresolveBveThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBveThreshold field is set.
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getPresolveBveThreshold
public int getPresolveBveThreshold()During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Specified by:
getPresolveBveThresholdin interfaceSatParametersOrBuilder- Returns:
- The presolveBveThreshold.
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setPresolveBveThreshold
During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Parameters:
value- The presolveBveThreshold to set.- Returns:
- This builder for chaining.
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clearPresolveBveThreshold
During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Returns:
- This builder for chaining.
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hasPresolveBveClauseWeight
public boolean hasPresolveBveClauseWeight()During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Specified by:
hasPresolveBveClauseWeightin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBveClauseWeight field is set.
-
getPresolveBveClauseWeight
public int getPresolveBveClauseWeight()During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Specified by:
getPresolveBveClauseWeightin interfaceSatParametersOrBuilder- Returns:
- The presolveBveClauseWeight.
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setPresolveBveClauseWeight
During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Parameters:
value- The presolveBveClauseWeight to set.- Returns:
- This builder for chaining.
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clearPresolveBveClauseWeight
During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Returns:
- This builder for chaining.
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hasPresolveProbingDeterministicTimeLimit
public boolean hasPresolveProbingDeterministicTimeLimit()The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing.
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Specified by:
hasPresolveProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveProbingDeterministicTimeLimit field is set.
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getPresolveProbingDeterministicTimeLimit
public double getPresolveProbingDeterministicTimeLimit()The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing.
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Specified by:
getPresolveProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- The presolveProbingDeterministicTimeLimit.
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setPresolveProbingDeterministicTimeLimit
The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing.
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Parameters:
value- The presolveProbingDeterministicTimeLimit to set.- Returns:
- This builder for chaining.
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clearPresolveProbingDeterministicTimeLimit
The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing.
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Returns:
- This builder for chaining.
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hasPresolveBlockedClause
public boolean hasPresolveBlockedClause()Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Specified by:
hasPresolveBlockedClausein interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBlockedClause field is set.
-
getPresolveBlockedClause
public boolean getPresolveBlockedClause()Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Specified by:
getPresolveBlockedClausein interfaceSatParametersOrBuilder- Returns:
- The presolveBlockedClause.
-
setPresolveBlockedClause
Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Parameters:
value- The presolveBlockedClause to set.- Returns:
- This builder for chaining.
-
clearPresolveBlockedClause
Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Returns:
- This builder for chaining.
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hasPresolveUseBva
public boolean hasPresolveUseBva()Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Specified by:
hasPresolveUseBvain interfaceSatParametersOrBuilder- Returns:
- Whether the presolveUseBva field is set.
-
getPresolveUseBva
public boolean getPresolveUseBva()Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Specified by:
getPresolveUseBvain interfaceSatParametersOrBuilder- Returns:
- The presolveUseBva.
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setPresolveUseBva
Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Parameters:
value- The presolveUseBva to set.- Returns:
- This builder for chaining.
-
clearPresolveUseBva
Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Returns:
- This builder for chaining.
-
hasPresolveBvaThreshold
public boolean hasPresolveBvaThreshold()Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Specified by:
hasPresolveBvaThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBvaThreshold field is set.
-
getPresolveBvaThreshold
public int getPresolveBvaThreshold()Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Specified by:
getPresolveBvaThresholdin interfaceSatParametersOrBuilder- Returns:
- The presolveBvaThreshold.
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setPresolveBvaThreshold
Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Parameters:
value- The presolveBvaThreshold to set.- Returns:
- This builder for chaining.
-
clearPresolveBvaThreshold
Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Returns:
- This builder for chaining.
-
hasMaxPresolveIterations
public boolean hasMaxPresolveIterations()In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Specified by:
hasMaxPresolveIterationsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxPresolveIterations field is set.
-
getMaxPresolveIterations
public int getMaxPresolveIterations()In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Specified by:
getMaxPresolveIterationsin interfaceSatParametersOrBuilder- Returns:
- The maxPresolveIterations.
-
setMaxPresolveIterations
In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Parameters:
value- The maxPresolveIterations to set.- Returns:
- This builder for chaining.
-
clearMaxPresolveIterations
In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Returns:
- This builder for chaining.
-
hasCpModelPresolve
public boolean hasCpModelPresolve()Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Specified by:
hasCpModelPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelPresolve field is set.
-
getCpModelPresolve
public boolean getCpModelPresolve()Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Specified by:
getCpModelPresolvein interfaceSatParametersOrBuilder- Returns:
- The cpModelPresolve.
-
setCpModelPresolve
Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Parameters:
value- The cpModelPresolve to set.- Returns:
- This builder for chaining.
-
clearCpModelPresolve
Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Returns:
- This builder for chaining.
-
hasCpModelProbingLevel
public boolean hasCpModelProbingLevel()How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Specified by:
hasCpModelProbingLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelProbingLevel field is set.
-
getCpModelProbingLevel
public int getCpModelProbingLevel()How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Specified by:
getCpModelProbingLevelin interfaceSatParametersOrBuilder- Returns:
- The cpModelProbingLevel.
-
setCpModelProbingLevel
How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Parameters:
value- The cpModelProbingLevel to set.- Returns:
- This builder for chaining.
-
clearCpModelProbingLevel
How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Returns:
- This builder for chaining.
-
hasCpModelUseSatPresolve
public boolean hasCpModelUseSatPresolve()Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Specified by:
hasCpModelUseSatPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelUseSatPresolve field is set.
-
getCpModelUseSatPresolve
public boolean getCpModelUseSatPresolve()Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Specified by:
getCpModelUseSatPresolvein interfaceSatParametersOrBuilder- Returns:
- The cpModelUseSatPresolve.
-
setCpModelUseSatPresolve
Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Parameters:
value- The cpModelUseSatPresolve to set.- Returns:
- This builder for chaining.
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clearCpModelUseSatPresolve
Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Returns:
- This builder for chaining.
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hasUseSatInprocessing
public boolean hasUseSatInprocessing()optional bool use_sat_inprocessing = 163 [default = false];- Specified by:
hasUseSatInprocessingin interfaceSatParametersOrBuilder- Returns:
- Whether the useSatInprocessing field is set.
-
getUseSatInprocessing
public boolean getUseSatInprocessing()optional bool use_sat_inprocessing = 163 [default = false];- Specified by:
getUseSatInprocessingin interfaceSatParametersOrBuilder- Returns:
- The useSatInprocessing.
-
setUseSatInprocessing
optional bool use_sat_inprocessing = 163 [default = false];- Parameters:
value- The useSatInprocessing to set.- Returns:
- This builder for chaining.
-
clearUseSatInprocessing
optional bool use_sat_inprocessing = 163 [default = false];- Returns:
- This builder for chaining.
-
hasDetectTableWithCost
public boolean hasDetectTableWithCost()If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Specified by:
hasDetectTableWithCostin interfaceSatParametersOrBuilder- Returns:
- Whether the detectTableWithCost field is set.
-
getDetectTableWithCost
public boolean getDetectTableWithCost()If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Specified by:
getDetectTableWithCostin interfaceSatParametersOrBuilder- Returns:
- The detectTableWithCost.
-
setDetectTableWithCost
If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Parameters:
value- The detectTableWithCost to set.- Returns:
- This builder for chaining.
-
clearDetectTableWithCost
If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Returns:
- This builder for chaining.
-
hasTableCompressionLevel
public boolean hasTableCompressionLevel()How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Specified by:
hasTableCompressionLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the tableCompressionLevel field is set.
-
getTableCompressionLevel
public int getTableCompressionLevel()How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Specified by:
getTableCompressionLevelin interfaceSatParametersOrBuilder- Returns:
- The tableCompressionLevel.
-
setTableCompressionLevel
How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Parameters:
value- The tableCompressionLevel to set.- Returns:
- This builder for chaining.
-
clearTableCompressionLevel
How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Returns:
- This builder for chaining.
-
hasExpandAlldiffConstraints
public boolean hasExpandAlldiffConstraints()If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Specified by:
hasExpandAlldiffConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the expandAlldiffConstraints field is set.
-
getExpandAlldiffConstraints
public boolean getExpandAlldiffConstraints()If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Specified by:
getExpandAlldiffConstraintsin interfaceSatParametersOrBuilder- Returns:
- The expandAlldiffConstraints.
-
setExpandAlldiffConstraints
If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Parameters:
value- The expandAlldiffConstraints to set.- Returns:
- This builder for chaining.
-
clearExpandAlldiffConstraints
If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Returns:
- This builder for chaining.
-
hasDisableConstraintExpansion
public boolean hasDisableConstraintExpansion()If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Specified by:
hasDisableConstraintExpansionin interfaceSatParametersOrBuilder- Returns:
- Whether the disableConstraintExpansion field is set.
-
getDisableConstraintExpansion
public boolean getDisableConstraintExpansion()If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Specified by:
getDisableConstraintExpansionin interfaceSatParametersOrBuilder- Returns:
- The disableConstraintExpansion.
-
setDisableConstraintExpansion
If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Parameters:
value- The disableConstraintExpansion to set.- Returns:
- This builder for chaining.
-
clearDisableConstraintExpansion
If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Returns:
- This builder for chaining.
-
hasMergeNoOverlapWorkLimit
public boolean hasMergeNoOverlapWorkLimit()During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Specified by:
hasMergeNoOverlapWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the mergeNoOverlapWorkLimit field is set.
-
getMergeNoOverlapWorkLimit
public double getMergeNoOverlapWorkLimit()During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Specified by:
getMergeNoOverlapWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The mergeNoOverlapWorkLimit.
-
setMergeNoOverlapWorkLimit
During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Parameters:
value- The mergeNoOverlapWorkLimit to set.- Returns:
- This builder for chaining.
-
clearMergeNoOverlapWorkLimit
During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Returns:
- This builder for chaining.
-
hasMergeAtMostOneWorkLimit
public boolean hasMergeAtMostOneWorkLimit()optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Specified by:
hasMergeAtMostOneWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the mergeAtMostOneWorkLimit field is set.
-
getMergeAtMostOneWorkLimit
public double getMergeAtMostOneWorkLimit()optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Specified by:
getMergeAtMostOneWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The mergeAtMostOneWorkLimit.
-
setMergeAtMostOneWorkLimit
optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Parameters:
value- The mergeAtMostOneWorkLimit to set.- Returns:
- This builder for chaining.
-
clearMergeAtMostOneWorkLimit
optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Returns:
- This builder for chaining.
-
hasPresolveSubstitutionLevel
public boolean hasPresolveSubstitutionLevel()How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Specified by:
hasPresolveSubstitutionLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveSubstitutionLevel field is set.
-
getPresolveSubstitutionLevel
public int getPresolveSubstitutionLevel()How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Specified by:
getPresolveSubstitutionLevelin interfaceSatParametersOrBuilder- Returns:
- The presolveSubstitutionLevel.
-
setPresolveSubstitutionLevel
How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Parameters:
value- The presolveSubstitutionLevel to set.- Returns:
- This builder for chaining.
-
clearPresolveSubstitutionLevel
How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Returns:
- This builder for chaining.
-
hasPresolveExtractIntegerEnforcement
public boolean hasPresolveExtractIntegerEnforcement()If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Specified by:
hasPresolveExtractIntegerEnforcementin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveExtractIntegerEnforcement field is set.
-
getPresolveExtractIntegerEnforcement
public boolean getPresolveExtractIntegerEnforcement()If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Specified by:
getPresolveExtractIntegerEnforcementin interfaceSatParametersOrBuilder- Returns:
- The presolveExtractIntegerEnforcement.
-
setPresolveExtractIntegerEnforcement
If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Parameters:
value- The presolveExtractIntegerEnforcement to set.- Returns:
- This builder for chaining.
-
clearPresolveExtractIntegerEnforcement
If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Returns:
- This builder for chaining.
-
hasPresolveInclusionWorkLimit
public boolean hasPresolveInclusionWorkLimit()A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Specified by:
hasPresolveInclusionWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveInclusionWorkLimit field is set.
-
getPresolveInclusionWorkLimit
public long getPresolveInclusionWorkLimit()A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Specified by:
getPresolveInclusionWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The presolveInclusionWorkLimit.
-
setPresolveInclusionWorkLimit
A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Parameters:
value- The presolveInclusionWorkLimit to set.- Returns:
- This builder for chaining.
-
clearPresolveInclusionWorkLimit
A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Returns:
- This builder for chaining.
-
hasIgnoreNames
public boolean hasIgnoreNames()If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Specified by:
hasIgnoreNamesin interfaceSatParametersOrBuilder- Returns:
- Whether the ignoreNames field is set.
-
getIgnoreNames
public boolean getIgnoreNames()If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Specified by:
getIgnoreNamesin interfaceSatParametersOrBuilder- Returns:
- The ignoreNames.
-
setIgnoreNames
If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Parameters:
value- The ignoreNames to set.- Returns:
- This builder for chaining.
-
clearIgnoreNames
If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Returns:
- This builder for chaining.
-
hasNumWorkers
public boolean hasNumWorkers()Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_worker'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Specified by:
hasNumWorkersin interfaceSatParametersOrBuilder- Returns:
- Whether the numWorkers field is set.
-
getNumWorkers
public int getNumWorkers()Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_worker'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Specified by:
getNumWorkersin interfaceSatParametersOrBuilder- Returns:
- The numWorkers.
-
setNumWorkers
Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_worker'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Parameters:
value- The numWorkers to set.- Returns:
- This builder for chaining.
-
clearNumWorkers
Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_worker'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Returns:
- This builder for chaining.
-
hasNumSearchWorkers
public boolean hasNumSearchWorkers()optional int32 num_search_workers = 100 [default = 0];- Specified by:
hasNumSearchWorkersin interfaceSatParametersOrBuilder- Returns:
- Whether the numSearchWorkers field is set.
-
getNumSearchWorkers
public int getNumSearchWorkers()optional int32 num_search_workers = 100 [default = 0];- Specified by:
getNumSearchWorkersin interfaceSatParametersOrBuilder- Returns:
- The numSearchWorkers.
-
setNumSearchWorkers
optional int32 num_search_workers = 100 [default = 0];- Parameters:
value- The numSearchWorkers to set.- Returns:
- This builder for chaining.
-
clearNumSearchWorkers
optional int32 num_search_workers = 100 [default = 0];- Returns:
- This builder for chaining.
-
hasMinNumLnsWorkers
public boolean hasMinNumLnsWorkers()If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread. TODO(user): Also define like for subsolvers the list of "active" type of neighborhood used.
optional int32 min_num_lns_workers = 211 [default = 2];- Specified by:
hasMinNumLnsWorkersin interfaceSatParametersOrBuilder- Returns:
- Whether the minNumLnsWorkers field is set.
-
getMinNumLnsWorkers
public int getMinNumLnsWorkers()If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread. TODO(user): Also define like for subsolvers the list of "active" type of neighborhood used.
optional int32 min_num_lns_workers = 211 [default = 2];- Specified by:
getMinNumLnsWorkersin interfaceSatParametersOrBuilder- Returns:
- The minNumLnsWorkers.
-
setMinNumLnsWorkers
If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread. TODO(user): Also define like for subsolvers the list of "active" type of neighborhood used.
optional int32 min_num_lns_workers = 211 [default = 2];- Parameters:
value- The minNumLnsWorkers to set.- Returns:
- This builder for chaining.
-
clearMinNumLnsWorkers
If there is an objective and we are not in interleave mode, we will reserve at least this number of worker for LNS thread. TODO(user): Also define like for subsolvers the list of "active" type of neighborhood used.
optional int32 min_num_lns_workers = 211 [default = 2];- Returns:
- This builder for chaining.
-
getSubsolversList
public com.google.protobuf.ProtocolStringList getSubsolversList()In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Specified by:
getSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the subsolvers.
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getSubsolversCount
public int getSubsolversCount()In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Specified by:
getSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of subsolvers.
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getSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Specified by:
getSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The subsolvers at the given index.
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getSubsolversBytes
public com.google.protobuf.ByteString getSubsolversBytes(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Specified by:
getSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the subsolvers at the given index.
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setSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Parameters:
index- The index to set the value at.value- The subsolvers to set.- Returns:
- This builder for chaining.
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addSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Parameters:
value- The subsolvers to add.- Returns:
- This builder for chaining.
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addAllSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Parameters:
values- The subsolvers to add.- Returns:
- This builder for chaining.
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clearSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Returns:
- This builder for chaining.
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addSubsolversBytes
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - less_encoding (only if no objective) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first usable "num_workers - min_num_lns_workers" subsolvers will be scheduled. You can see in the log which one are selected for a given run. All the others will be LNS if there is an objective, or randomized SAT search for pure satisfiability problems.
repeated string subsolvers = 207;- Parameters:
value- The bytes of the subsolvers to add.- Returns:
- This builder for chaining.
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getExtraSubsolversList
public com.google.protobuf.ProtocolStringList getExtraSubsolversList()A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the extraSubsolvers.
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getExtraSubsolversCount
public int getExtraSubsolversCount()A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of extraSubsolvers.
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getExtraSubsolvers
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The extraSubsolvers at the given index.
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getExtraSubsolversBytes
public com.google.protobuf.ByteString getExtraSubsolversBytes(int index) A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the extraSubsolvers at the given index.
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setExtraSubsolvers
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Parameters:
index- The index to set the value at.value- The extraSubsolvers to set.- Returns:
- This builder for chaining.
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addExtraSubsolvers
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Parameters:
value- The extraSubsolvers to add.- Returns:
- This builder for chaining.
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addAllExtraSubsolvers
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Parameters:
values- The extraSubsolvers to add.- Returns:
- This builder for chaining.
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clearExtraSubsolvers
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Returns:
- This builder for chaining.
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addExtraSubsolversBytes
A convenient way to add more workers types. Note that these will be added at the end of the list, so this is only useful if you run with many workers.
repeated string extra_subsolvers = 219;- Parameters:
value- The bytes of the extraSubsolvers to add.- Returns:
- This builder for chaining.
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getIgnoreSubsolversList
public com.google.protobuf.ProtocolStringList getIgnoreSubsolversList()Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the ignoreSubsolvers.
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getIgnoreSubsolversCount
public int getIgnoreSubsolversCount()Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of ignoreSubsolvers.
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getIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The ignoreSubsolvers at the given index.
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getIgnoreSubsolversBytes
public com.google.protobuf.ByteString getIgnoreSubsolversBytes(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the ignoreSubsolvers at the given index.
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setIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Parameters:
index- The index to set the value at.value- The ignoreSubsolvers to set.- Returns:
- This builder for chaining.
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addIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Parameters:
value- The ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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addAllIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Parameters:
values- The ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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clearIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Returns:
- This builder for chaining.
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addIgnoreSubsolversBytes
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem.
repeated string ignore_subsolvers = 209;- Parameters:
value- The bytes of the ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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getSubsolverParamsList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsListin interfaceSatParametersOrBuilder
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getSubsolverParamsCount
public int getSubsolverParamsCount()It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsCountin interfaceSatParametersOrBuilder
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getSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsin interfaceSatParametersOrBuilder
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setSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
setSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addAllSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
clearSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
removeSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsOrBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsOrBuilderin interfaceSatParametersOrBuilder
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getSubsolverParamsOrBuilderList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsOrBuilderListin interfaceSatParametersOrBuilder
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addSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsBuilderList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. It is also possible to overwrite the default names above.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
hasInterleaveSearch
public boolean hasInterleaveSearch()Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Specified by:
hasInterleaveSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the interleaveSearch field is set.
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getInterleaveSearch
public boolean getInterleaveSearch()Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Specified by:
getInterleaveSearchin interfaceSatParametersOrBuilder- Returns:
- The interleaveSearch.
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setInterleaveSearch
Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Parameters:
value- The interleaveSearch to set.- Returns:
- This builder for chaining.
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clearInterleaveSearch
Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Returns:
- This builder for chaining.
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hasInterleaveBatchSize
public boolean hasInterleaveBatchSize()optional int32 interleave_batch_size = 134 [default = 1];- Specified by:
hasInterleaveBatchSizein interfaceSatParametersOrBuilder- Returns:
- Whether the interleaveBatchSize field is set.
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getInterleaveBatchSize
public int getInterleaveBatchSize()optional int32 interleave_batch_size = 134 [default = 1];- Specified by:
getInterleaveBatchSizein interfaceSatParametersOrBuilder- Returns:
- The interleaveBatchSize.
-
setInterleaveBatchSize
optional int32 interleave_batch_size = 134 [default = 1];- Parameters:
value- The interleaveBatchSize to set.- Returns:
- This builder for chaining.
-
clearInterleaveBatchSize
optional int32 interleave_batch_size = 134 [default = 1];- Returns:
- This builder for chaining.
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hasDebugPostsolveWithFullSolver
public boolean hasDebugPostsolveWithFullSolver()We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Specified by:
hasDebugPostsolveWithFullSolverin interfaceSatParametersOrBuilder- Returns:
- Whether the debugPostsolveWithFullSolver field is set.
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getDebugPostsolveWithFullSolver
public boolean getDebugPostsolveWithFullSolver()We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Specified by:
getDebugPostsolveWithFullSolverin interfaceSatParametersOrBuilder- Returns:
- The debugPostsolveWithFullSolver.
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setDebugPostsolveWithFullSolver
We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Parameters:
value- The debugPostsolveWithFullSolver to set.- Returns:
- This builder for chaining.
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clearDebugPostsolveWithFullSolver
We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Returns:
- This builder for chaining.
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hasDebugMaxNumPresolveOperations
public boolean hasDebugMaxNumPresolveOperations()If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Specified by:
hasDebugMaxNumPresolveOperationsin interfaceSatParametersOrBuilder- Returns:
- Whether the debugMaxNumPresolveOperations field is set.
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getDebugMaxNumPresolveOperations
public int getDebugMaxNumPresolveOperations()If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Specified by:
getDebugMaxNumPresolveOperationsin interfaceSatParametersOrBuilder- Returns:
- The debugMaxNumPresolveOperations.
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setDebugMaxNumPresolveOperations
If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Parameters:
value- The debugMaxNumPresolveOperations to set.- Returns:
- This builder for chaining.
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clearDebugMaxNumPresolveOperations
If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Returns:
- This builder for chaining.
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hasDebugCrashOnBadHint
public boolean hasDebugCrashOnBadHint()Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Specified by:
hasDebugCrashOnBadHintin interfaceSatParametersOrBuilder- Returns:
- Whether the debugCrashOnBadHint field is set.
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getDebugCrashOnBadHint
public boolean getDebugCrashOnBadHint()Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Specified by:
getDebugCrashOnBadHintin interfaceSatParametersOrBuilder- Returns:
- The debugCrashOnBadHint.
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setDebugCrashOnBadHint
Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Parameters:
value- The debugCrashOnBadHint to set.- Returns:
- This builder for chaining.
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clearDebugCrashOnBadHint
Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Returns:
- This builder for chaining.
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hasUseOptimizationHints
public boolean hasUseOptimizationHints()For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Specified by:
hasUseOptimizationHintsin interfaceSatParametersOrBuilder- Returns:
- Whether the useOptimizationHints field is set.
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getUseOptimizationHints
public boolean getUseOptimizationHints()For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Specified by:
getUseOptimizationHintsin interfaceSatParametersOrBuilder- Returns:
- The useOptimizationHints.
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setUseOptimizationHints
For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Parameters:
value- The useOptimizationHints to set.- Returns:
- This builder for chaining.
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clearUseOptimizationHints
For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Returns:
- This builder for chaining.
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hasMinimizeCore
public boolean hasMinimizeCore()Whether we use a simple heuristic to try to minimize an UNSAT core.
optional bool minimize_core = 50 [default = true];- Specified by:
hasMinimizeCorein interfaceSatParametersOrBuilder- Returns:
- Whether the minimizeCore field is set.
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getMinimizeCore
public boolean getMinimizeCore()Whether we use a simple heuristic to try to minimize an UNSAT core.
optional bool minimize_core = 50 [default = true];- Specified by:
getMinimizeCorein interfaceSatParametersOrBuilder- Returns:
- The minimizeCore.
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setMinimizeCore
Whether we use a simple heuristic to try to minimize an UNSAT core.
optional bool minimize_core = 50 [default = true];- Parameters:
value- The minimizeCore to set.- Returns:
- This builder for chaining.
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clearMinimizeCore
Whether we use a simple heuristic to try to minimize an UNSAT core.
optional bool minimize_core = 50 [default = true];- Returns:
- This builder for chaining.
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hasFindMultipleCores
public boolean hasFindMultipleCores()Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Specified by:
hasFindMultipleCoresin interfaceSatParametersOrBuilder- Returns:
- Whether the findMultipleCores field is set.
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getFindMultipleCores
public boolean getFindMultipleCores()Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Specified by:
getFindMultipleCoresin interfaceSatParametersOrBuilder- Returns:
- The findMultipleCores.
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setFindMultipleCores
Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Parameters:
value- The findMultipleCores to set.- Returns:
- This builder for chaining.
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clearFindMultipleCores
Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Returns:
- This builder for chaining.
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hasCoverOptimization
public boolean hasCoverOptimization()If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Specified by:
hasCoverOptimizationin interfaceSatParametersOrBuilder- Returns:
- Whether the coverOptimization field is set.
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getCoverOptimization
public boolean getCoverOptimization()If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Specified by:
getCoverOptimizationin interfaceSatParametersOrBuilder- Returns:
- The coverOptimization.
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setCoverOptimization
If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Parameters:
value- The coverOptimization to set.- Returns:
- This builder for chaining.
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clearCoverOptimization
If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Returns:
- This builder for chaining.
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hasMaxSatAssumptionOrder
public boolean hasMaxSatAssumptionOrder()optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Specified by:
hasMaxSatAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatAssumptionOrder field is set.
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getMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Specified by:
getMaxSatAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- The maxSatAssumptionOrder.
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setMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Parameters:
value- The maxSatAssumptionOrder to set.- Returns:
- This builder for chaining.
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clearMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Returns:
- This builder for chaining.
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hasMaxSatReverseAssumptionOrder
public boolean hasMaxSatReverseAssumptionOrder()If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Specified by:
hasMaxSatReverseAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatReverseAssumptionOrder field is set.
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getMaxSatReverseAssumptionOrder
public boolean getMaxSatReverseAssumptionOrder()If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Specified by:
getMaxSatReverseAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- The maxSatReverseAssumptionOrder.
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setMaxSatReverseAssumptionOrder
If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Parameters:
value- The maxSatReverseAssumptionOrder to set.- Returns:
- This builder for chaining.
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clearMaxSatReverseAssumptionOrder
If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Returns:
- This builder for chaining.
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hasMaxSatStratification
public boolean hasMaxSatStratification()optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Specified by:
hasMaxSatStratificationin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatStratification field is set.
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getMaxSatStratification
optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Specified by:
getMaxSatStratificationin interfaceSatParametersOrBuilder- Returns:
- The maxSatStratification.
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setMaxSatStratification
public SatParameters.Builder setMaxSatStratification(SatParameters.MaxSatStratificationAlgorithm value) optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Parameters:
value- The maxSatStratification to set.- Returns:
- This builder for chaining.
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clearMaxSatStratification
optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Returns:
- This builder for chaining.
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hasPropagationLoopDetectionFactor
public boolean hasPropagationLoopDetectionFactor()Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Specified by:
hasPropagationLoopDetectionFactorin interfaceSatParametersOrBuilder- Returns:
- Whether the propagationLoopDetectionFactor field is set.
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getPropagationLoopDetectionFactor
public double getPropagationLoopDetectionFactor()Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Specified by:
getPropagationLoopDetectionFactorin interfaceSatParametersOrBuilder- Returns:
- The propagationLoopDetectionFactor.
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setPropagationLoopDetectionFactor
Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Parameters:
value- The propagationLoopDetectionFactor to set.- Returns:
- This builder for chaining.
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clearPropagationLoopDetectionFactor
Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Returns:
- This builder for chaining.
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hasUsePrecedencesInDisjunctiveConstraint
public boolean hasUsePrecedencesInDisjunctiveConstraint()When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Specified by:
hasUsePrecedencesInDisjunctiveConstraintin interfaceSatParametersOrBuilder- Returns:
- Whether the usePrecedencesInDisjunctiveConstraint field is set.
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getUsePrecedencesInDisjunctiveConstraint
public boolean getUsePrecedencesInDisjunctiveConstraint()When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Specified by:
getUsePrecedencesInDisjunctiveConstraintin interfaceSatParametersOrBuilder- Returns:
- The usePrecedencesInDisjunctiveConstraint.
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setUsePrecedencesInDisjunctiveConstraint
When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Parameters:
value- The usePrecedencesInDisjunctiveConstraint to set.- Returns:
- This builder for chaining.
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clearUsePrecedencesInDisjunctiveConstraint
When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Returns:
- This builder for chaining.
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hasUseOverloadCheckerInCumulative
public boolean hasUseOverloadCheckerInCumulative()When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Specified by:
hasUseOverloadCheckerInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useOverloadCheckerInCumulative field is set.
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getUseOverloadCheckerInCumulative
public boolean getUseOverloadCheckerInCumulative()When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Specified by:
getUseOverloadCheckerInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useOverloadCheckerInCumulative.
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setUseOverloadCheckerInCumulative
When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Parameters:
value- The useOverloadCheckerInCumulative to set.- Returns:
- This builder for chaining.
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clearUseOverloadCheckerInCumulative
When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Returns:
- This builder for chaining.
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hasUseTimetableEdgeFindingInCumulative
public boolean hasUseTimetableEdgeFindingInCumulative()When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Specified by:
hasUseTimetableEdgeFindingInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useTimetableEdgeFindingInCumulative field is set.
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getUseTimetableEdgeFindingInCumulative
public boolean getUseTimetableEdgeFindingInCumulative()When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Specified by:
getUseTimetableEdgeFindingInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useTimetableEdgeFindingInCumulative.
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setUseTimetableEdgeFindingInCumulative
When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Parameters:
value- The useTimetableEdgeFindingInCumulative to set.- Returns:
- This builder for chaining.
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clearUseTimetableEdgeFindingInCumulative
When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Returns:
- This builder for chaining.
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hasUseHardPrecedencesInCumulative
public boolean hasUseHardPrecedencesInCumulative()If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Specified by:
hasUseHardPrecedencesInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useHardPrecedencesInCumulative field is set.
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getUseHardPrecedencesInCumulative
public boolean getUseHardPrecedencesInCumulative()If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Specified by:
getUseHardPrecedencesInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useHardPrecedencesInCumulative.
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setUseHardPrecedencesInCumulative
If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Parameters:
value- The useHardPrecedencesInCumulative to set.- Returns:
- This builder for chaining.
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clearUseHardPrecedencesInCumulative
If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Returns:
- This builder for chaining.
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hasExploitAllPrecedences
public boolean hasExploitAllPrecedences()optional bool exploit_all_precedences = 220 [default = false];- Specified by:
hasExploitAllPrecedencesin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitAllPrecedences field is set.
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getExploitAllPrecedences
public boolean getExploitAllPrecedences()optional bool exploit_all_precedences = 220 [default = false];- Specified by:
getExploitAllPrecedencesin interfaceSatParametersOrBuilder- Returns:
- The exploitAllPrecedences.
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setExploitAllPrecedences
optional bool exploit_all_precedences = 220 [default = false];- Parameters:
value- The exploitAllPrecedences to set.- Returns:
- This builder for chaining.
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clearExploitAllPrecedences
optional bool exploit_all_precedences = 220 [default = false];- Returns:
- This builder for chaining.
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hasUseDisjunctiveConstraintInCumulative
public boolean hasUseDisjunctiveConstraintInCumulative()When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Specified by:
hasUseDisjunctiveConstraintInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useDisjunctiveConstraintInCumulative field is set.
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getUseDisjunctiveConstraintInCumulative
public boolean getUseDisjunctiveConstraintInCumulative()When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Specified by:
getUseDisjunctiveConstraintInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useDisjunctiveConstraintInCumulative.
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setUseDisjunctiveConstraintInCumulative
When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Parameters:
value- The useDisjunctiveConstraintInCumulative to set.- Returns:
- This builder for chaining.
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clearUseDisjunctiveConstraintInCumulative
When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Returns:
- This builder for chaining.
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hasUseTimetablingInNoOverlap2D
public boolean hasUseTimetablingInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Specified by:
hasUseTimetablingInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useTimetablingInNoOverlap2d field is set.
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getUseTimetablingInNoOverlap2D
public boolean getUseTimetablingInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Specified by:
getUseTimetablingInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useTimetablingInNoOverlap2d.
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setUseTimetablingInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Parameters:
value- The useTimetablingInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseTimetablingInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Returns:
- This builder for chaining.
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hasUseEnergeticReasoningInNoOverlap2D
public boolean hasUseEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Specified by:
hasUseEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useEnergeticReasoningInNoOverlap2d field is set.
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getUseEnergeticReasoningInNoOverlap2D
public boolean getUseEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Specified by:
getUseEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useEnergeticReasoningInNoOverlap2d.
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setUseEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Parameters:
value- The useEnergeticReasoningInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Returns:
- This builder for chaining.
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hasUseDualSchedulingHeuristics
public boolean hasUseDualSchedulingHeuristics()When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Specified by:
hasUseDualSchedulingHeuristicsin interfaceSatParametersOrBuilder- Returns:
- Whether the useDualSchedulingHeuristics field is set.
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getUseDualSchedulingHeuristics
public boolean getUseDualSchedulingHeuristics()When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Specified by:
getUseDualSchedulingHeuristicsin interfaceSatParametersOrBuilder- Returns:
- The useDualSchedulingHeuristics.
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setUseDualSchedulingHeuristics
When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Parameters:
value- The useDualSchedulingHeuristics to set.- Returns:
- This builder for chaining.
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clearUseDualSchedulingHeuristics
When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Returns:
- This builder for chaining.
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hasLinearizationLevel
public boolean hasLinearizationLevel()A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Specified by:
hasLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the linearizationLevel field is set.
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getLinearizationLevel
public int getLinearizationLevel()A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Specified by:
getLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- The linearizationLevel.
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setLinearizationLevel
A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Parameters:
value- The linearizationLevel to set.- Returns:
- This builder for chaining.
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clearLinearizationLevel
A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Returns:
- This builder for chaining.
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hasBooleanEncodingLevel
public boolean hasBooleanEncodingLevel()A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Specified by:
hasBooleanEncodingLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the booleanEncodingLevel field is set.
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getBooleanEncodingLevel
public int getBooleanEncodingLevel()A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Specified by:
getBooleanEncodingLevelin interfaceSatParametersOrBuilder- Returns:
- The booleanEncodingLevel.
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setBooleanEncodingLevel
A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Parameters:
value- The booleanEncodingLevel to set.- Returns:
- This builder for chaining.
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clearBooleanEncodingLevel
A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Returns:
- This builder for chaining.
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hasMaxDomainSizeWhenEncodingEqNeqConstraints
public boolean hasMaxDomainSizeWhenEncodingEqNeqConstraints()When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Specified by:
hasMaxDomainSizeWhenEncodingEqNeqConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxDomainSizeWhenEncodingEqNeqConstraints field is set.
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getMaxDomainSizeWhenEncodingEqNeqConstraints
public int getMaxDomainSizeWhenEncodingEqNeqConstraints()When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Specified by:
getMaxDomainSizeWhenEncodingEqNeqConstraintsin interfaceSatParametersOrBuilder- Returns:
- The maxDomainSizeWhenEncodingEqNeqConstraints.
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setMaxDomainSizeWhenEncodingEqNeqConstraints
When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Parameters:
value- The maxDomainSizeWhenEncodingEqNeqConstraints to set.- Returns:
- This builder for chaining.
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clearMaxDomainSizeWhenEncodingEqNeqConstraints
When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Returns:
- This builder for chaining.
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hasMaxNumCuts
public boolean hasMaxNumCuts()The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Specified by:
hasMaxNumCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumCuts field is set.
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getMaxNumCuts
public int getMaxNumCuts()The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Specified by:
getMaxNumCutsin interfaceSatParametersOrBuilder- Returns:
- The maxNumCuts.
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setMaxNumCuts
The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Parameters:
value- The maxNumCuts to set.- Returns:
- This builder for chaining.
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clearMaxNumCuts
The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Returns:
- This builder for chaining.
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hasCutLevel
public boolean hasCutLevel()Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Specified by:
hasCutLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the cutLevel field is set.
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getCutLevel
public int getCutLevel()Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Specified by:
getCutLevelin interfaceSatParametersOrBuilder- Returns:
- The cutLevel.
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setCutLevel
Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Parameters:
value- The cutLevel to set.- Returns:
- This builder for chaining.
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clearCutLevel
Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Returns:
- This builder for chaining.
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hasOnlyAddCutsAtLevelZero
public boolean hasOnlyAddCutsAtLevelZero()For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Specified by:
hasOnlyAddCutsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- Whether the onlyAddCutsAtLevelZero field is set.
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getOnlyAddCutsAtLevelZero
public boolean getOnlyAddCutsAtLevelZero()For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Specified by:
getOnlyAddCutsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- The onlyAddCutsAtLevelZero.
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setOnlyAddCutsAtLevelZero
For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Parameters:
value- The onlyAddCutsAtLevelZero to set.- Returns:
- This builder for chaining.
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clearOnlyAddCutsAtLevelZero
For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Returns:
- This builder for chaining.
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hasAddObjectiveCut
public boolean hasAddObjectiveCut()When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Specified by:
hasAddObjectiveCutin interfaceSatParametersOrBuilder- Returns:
- Whether the addObjectiveCut field is set.
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getAddObjectiveCut
public boolean getAddObjectiveCut()When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Specified by:
getAddObjectiveCutin interfaceSatParametersOrBuilder- Returns:
- The addObjectiveCut.
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setAddObjectiveCut
When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Parameters:
value- The addObjectiveCut to set.- Returns:
- This builder for chaining.
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clearAddObjectiveCut
When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Returns:
- This builder for chaining.
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hasAddCgCuts
public boolean hasAddCgCuts()Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Specified by:
hasAddCgCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addCgCuts field is set.
-
getAddCgCuts
public boolean getAddCgCuts()Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Specified by:
getAddCgCutsin interfaceSatParametersOrBuilder- Returns:
- The addCgCuts.
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setAddCgCuts
Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Parameters:
value- The addCgCuts to set.- Returns:
- This builder for chaining.
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clearAddCgCuts
Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Returns:
- This builder for chaining.
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hasAddMirCuts
public boolean hasAddMirCuts()Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Specified by:
hasAddMirCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addMirCuts field is set.
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getAddMirCuts
public boolean getAddMirCuts()Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Specified by:
getAddMirCutsin interfaceSatParametersOrBuilder- Returns:
- The addMirCuts.
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setAddMirCuts
Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Parameters:
value- The addMirCuts to set.- Returns:
- This builder for chaining.
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clearAddMirCuts
Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Returns:
- This builder for chaining.
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hasAddZeroHalfCuts
public boolean hasAddZeroHalfCuts()Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Specified by:
hasAddZeroHalfCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addZeroHalfCuts field is set.
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getAddZeroHalfCuts
public boolean getAddZeroHalfCuts()Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Specified by:
getAddZeroHalfCutsin interfaceSatParametersOrBuilder- Returns:
- The addZeroHalfCuts.
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setAddZeroHalfCuts
Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Parameters:
value- The addZeroHalfCuts to set.- Returns:
- This builder for chaining.
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clearAddZeroHalfCuts
Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Returns:
- This builder for chaining.
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hasAddCliqueCuts
public boolean hasAddCliqueCuts()Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Specified by:
hasAddCliqueCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addCliqueCuts field is set.
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getAddCliqueCuts
public boolean getAddCliqueCuts()Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Specified by:
getAddCliqueCutsin interfaceSatParametersOrBuilder- Returns:
- The addCliqueCuts.
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setAddCliqueCuts
Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Parameters:
value- The addCliqueCuts to set.- Returns:
- This builder for chaining.
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clearAddCliqueCuts
Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Returns:
- This builder for chaining.
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hasMaxAllDiffCutSize
public boolean hasMaxAllDiffCutSize()Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 7];- Specified by:
hasMaxAllDiffCutSizein interfaceSatParametersOrBuilder- Returns:
- Whether the maxAllDiffCutSize field is set.
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getMaxAllDiffCutSize
public int getMaxAllDiffCutSize()Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 7];- Specified by:
getMaxAllDiffCutSizein interfaceSatParametersOrBuilder- Returns:
- The maxAllDiffCutSize.
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setMaxAllDiffCutSize
Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 7];- Parameters:
value- The maxAllDiffCutSize to set.- Returns:
- This builder for chaining.
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clearMaxAllDiffCutSize
Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 7];- Returns:
- This builder for chaining.
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hasAddLinMaxCuts
public boolean hasAddLinMaxCuts()For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Specified by:
hasAddLinMaxCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addLinMaxCuts field is set.
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getAddLinMaxCuts
public boolean getAddLinMaxCuts()For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Specified by:
getAddLinMaxCutsin interfaceSatParametersOrBuilder- Returns:
- The addLinMaxCuts.
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setAddLinMaxCuts
For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Parameters:
value- The addLinMaxCuts to set.- Returns:
- This builder for chaining.
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clearAddLinMaxCuts
For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Returns:
- This builder for chaining.
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hasMaxIntegerRoundingScaling
public boolean hasMaxIntegerRoundingScaling()In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Specified by:
hasMaxIntegerRoundingScalingin interfaceSatParametersOrBuilder- Returns:
- Whether the maxIntegerRoundingScaling field is set.
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getMaxIntegerRoundingScaling
public int getMaxIntegerRoundingScaling()In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Specified by:
getMaxIntegerRoundingScalingin interfaceSatParametersOrBuilder- Returns:
- The maxIntegerRoundingScaling.
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setMaxIntegerRoundingScaling
In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Parameters:
value- The maxIntegerRoundingScaling to set.- Returns:
- This builder for chaining.
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clearMaxIntegerRoundingScaling
In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Returns:
- This builder for chaining.
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hasAddLpConstraintsLazily
public boolean hasAddLpConstraintsLazily()If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Specified by:
hasAddLpConstraintsLazilyin interfaceSatParametersOrBuilder- Returns:
- Whether the addLpConstraintsLazily field is set.
-
getAddLpConstraintsLazily
public boolean getAddLpConstraintsLazily()If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Specified by:
getAddLpConstraintsLazilyin interfaceSatParametersOrBuilder- Returns:
- The addLpConstraintsLazily.
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setAddLpConstraintsLazily
If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Parameters:
value- The addLpConstraintsLazily to set.- Returns:
- This builder for chaining.
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clearAddLpConstraintsLazily
If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Returns:
- This builder for chaining.
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hasMinOrthogonalityForLpConstraints
public boolean hasMinOrthogonalityForLpConstraints()While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Specified by:
hasMinOrthogonalityForLpConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the minOrthogonalityForLpConstraints field is set.
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getMinOrthogonalityForLpConstraints
public double getMinOrthogonalityForLpConstraints()While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Specified by:
getMinOrthogonalityForLpConstraintsin interfaceSatParametersOrBuilder- Returns:
- The minOrthogonalityForLpConstraints.
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setMinOrthogonalityForLpConstraints
While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Parameters:
value- The minOrthogonalityForLpConstraints to set.- Returns:
- This builder for chaining.
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clearMinOrthogonalityForLpConstraints
While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Returns:
- This builder for chaining.
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hasMaxCutRoundsAtLevelZero
public boolean hasMaxCutRoundsAtLevelZero()Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Specified by:
hasMaxCutRoundsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- Whether the maxCutRoundsAtLevelZero field is set.
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getMaxCutRoundsAtLevelZero
public int getMaxCutRoundsAtLevelZero()Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Specified by:
getMaxCutRoundsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- The maxCutRoundsAtLevelZero.
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setMaxCutRoundsAtLevelZero
Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Parameters:
value- The maxCutRoundsAtLevelZero to set.- Returns:
- This builder for chaining.
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clearMaxCutRoundsAtLevelZero
Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Returns:
- This builder for chaining.
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hasMaxConsecutiveInactiveCount
public boolean hasMaxConsecutiveInactiveCount()If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Specified by:
hasMaxConsecutiveInactiveCountin interfaceSatParametersOrBuilder- Returns:
- Whether the maxConsecutiveInactiveCount field is set.
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getMaxConsecutiveInactiveCount
public int getMaxConsecutiveInactiveCount()If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Specified by:
getMaxConsecutiveInactiveCountin interfaceSatParametersOrBuilder- Returns:
- The maxConsecutiveInactiveCount.
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setMaxConsecutiveInactiveCount
If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Parameters:
value- The maxConsecutiveInactiveCount to set.- Returns:
- This builder for chaining.
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clearMaxConsecutiveInactiveCount
If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Returns:
- This builder for chaining.
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hasCutMaxActiveCountValue
public boolean hasCutMaxActiveCountValue()These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Specified by:
hasCutMaxActiveCountValuein interfaceSatParametersOrBuilder- Returns:
- Whether the cutMaxActiveCountValue field is set.
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getCutMaxActiveCountValue
public double getCutMaxActiveCountValue()These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Specified by:
getCutMaxActiveCountValuein interfaceSatParametersOrBuilder- Returns:
- The cutMaxActiveCountValue.
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setCutMaxActiveCountValue
These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Parameters:
value- The cutMaxActiveCountValue to set.- Returns:
- This builder for chaining.
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clearCutMaxActiveCountValue
These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Returns:
- This builder for chaining.
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hasCutActiveCountDecay
public boolean hasCutActiveCountDecay()optional double cut_active_count_decay = 156 [default = 0.8];- Specified by:
hasCutActiveCountDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the cutActiveCountDecay field is set.
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getCutActiveCountDecay
public double getCutActiveCountDecay()optional double cut_active_count_decay = 156 [default = 0.8];- Specified by:
getCutActiveCountDecayin interfaceSatParametersOrBuilder- Returns:
- The cutActiveCountDecay.
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setCutActiveCountDecay
optional double cut_active_count_decay = 156 [default = 0.8];- Parameters:
value- The cutActiveCountDecay to set.- Returns:
- This builder for chaining.
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clearCutActiveCountDecay
optional double cut_active_count_decay = 156 [default = 0.8];- Returns:
- This builder for chaining.
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hasCutCleanupTarget
public boolean hasCutCleanupTarget()Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Specified by:
hasCutCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- Whether the cutCleanupTarget field is set.
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getCutCleanupTarget
public int getCutCleanupTarget()Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Specified by:
getCutCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- The cutCleanupTarget.
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setCutCleanupTarget
Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Parameters:
value- The cutCleanupTarget to set.- Returns:
- This builder for chaining.
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clearCutCleanupTarget
Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Returns:
- This builder for chaining.
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hasNewConstraintsBatchSize
public boolean hasNewConstraintsBatchSize()Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Specified by:
hasNewConstraintsBatchSizein interfaceSatParametersOrBuilder- Returns:
- Whether the newConstraintsBatchSize field is set.
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getNewConstraintsBatchSize
public int getNewConstraintsBatchSize()Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Specified by:
getNewConstraintsBatchSizein interfaceSatParametersOrBuilder- Returns:
- The newConstraintsBatchSize.
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setNewConstraintsBatchSize
Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Parameters:
value- The newConstraintsBatchSize to set.- Returns:
- This builder for chaining.
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clearNewConstraintsBatchSize
Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Returns:
- This builder for chaining.
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hasSearchBranching
public boolean hasSearchBranching()optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Specified by:
hasSearchBranchingin interfaceSatParametersOrBuilder- Returns:
- Whether the searchBranching field is set.
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getSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Specified by:
getSearchBranchingin interfaceSatParametersOrBuilder- Returns:
- The searchBranching.
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setSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Parameters:
value- The searchBranching to set.- Returns:
- This builder for chaining.
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clearSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Returns:
- This builder for chaining.
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hasHintConflictLimit
public boolean hasHintConflictLimit()Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Specified by:
hasHintConflictLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the hintConflictLimit field is set.
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getHintConflictLimit
public int getHintConflictLimit()Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Specified by:
getHintConflictLimitin interfaceSatParametersOrBuilder- Returns:
- The hintConflictLimit.
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setHintConflictLimit
Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Parameters:
value- The hintConflictLimit to set.- Returns:
- This builder for chaining.
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clearHintConflictLimit
Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Returns:
- This builder for chaining.
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hasRepairHint
public boolean hasRepairHint()If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Specified by:
hasRepairHintin interfaceSatParametersOrBuilder- Returns:
- Whether the repairHint field is set.
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getRepairHint
public boolean getRepairHint()If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Specified by:
getRepairHintin interfaceSatParametersOrBuilder- Returns:
- The repairHint.
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setRepairHint
If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Parameters:
value- The repairHint to set.- Returns:
- This builder for chaining.
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clearRepairHint
If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Returns:
- This builder for chaining.
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hasFixVariablesToTheirHintedValue
public boolean hasFixVariablesToTheirHintedValue()If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Specified by:
hasFixVariablesToTheirHintedValuein interfaceSatParametersOrBuilder- Returns:
- Whether the fixVariablesToTheirHintedValue field is set.
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getFixVariablesToTheirHintedValue
public boolean getFixVariablesToTheirHintedValue()If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Specified by:
getFixVariablesToTheirHintedValuein interfaceSatParametersOrBuilder- Returns:
- The fixVariablesToTheirHintedValue.
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setFixVariablesToTheirHintedValue
If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Parameters:
value- The fixVariablesToTheirHintedValue to set.- Returns:
- This builder for chaining.
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clearFixVariablesToTheirHintedValue
If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Returns:
- This builder for chaining.
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hasExploitIntegerLpSolution
public boolean hasExploitIntegerLpSolution()If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Specified by:
hasExploitIntegerLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitIntegerLpSolution field is set.
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getExploitIntegerLpSolution
public boolean getExploitIntegerLpSolution()If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Specified by:
getExploitIntegerLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitIntegerLpSolution.
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setExploitIntegerLpSolution
If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Parameters:
value- The exploitIntegerLpSolution to set.- Returns:
- This builder for chaining.
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clearExploitIntegerLpSolution
If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Returns:
- This builder for chaining.
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hasExploitAllLpSolution
public boolean hasExploitAllLpSolution()If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Specified by:
hasExploitAllLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitAllLpSolution field is set.
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getExploitAllLpSolution
public boolean getExploitAllLpSolution()If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Specified by:
getExploitAllLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitAllLpSolution.
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setExploitAllLpSolution
If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Parameters:
value- The exploitAllLpSolution to set.- Returns:
- This builder for chaining.
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clearExploitAllLpSolution
If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Returns:
- This builder for chaining.
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hasExploitBestSolution
public boolean hasExploitBestSolution()When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Specified by:
hasExploitBestSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitBestSolution field is set.
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getExploitBestSolution
public boolean getExploitBestSolution()When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Specified by:
getExploitBestSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitBestSolution.
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setExploitBestSolution
When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Parameters:
value- The exploitBestSolution to set.- Returns:
- This builder for chaining.
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clearExploitBestSolution
When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Returns:
- This builder for chaining.
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hasExploitRelaxationSolution
public boolean hasExploitRelaxationSolution()When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Specified by:
hasExploitRelaxationSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitRelaxationSolution field is set.
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getExploitRelaxationSolution
public boolean getExploitRelaxationSolution()When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Specified by:
getExploitRelaxationSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitRelaxationSolution.
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setExploitRelaxationSolution
When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Parameters:
value- The exploitRelaxationSolution to set.- Returns:
- This builder for chaining.
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clearExploitRelaxationSolution
When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Returns:
- This builder for chaining.
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hasExploitObjective
public boolean hasExploitObjective()When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Specified by:
hasExploitObjectivein interfaceSatParametersOrBuilder- Returns:
- Whether the exploitObjective field is set.
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getExploitObjective
public boolean getExploitObjective()When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Specified by:
getExploitObjectivein interfaceSatParametersOrBuilder- Returns:
- The exploitObjective.
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setExploitObjective
When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Parameters:
value- The exploitObjective to set.- Returns:
- This builder for chaining.
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clearExploitObjective
When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Returns:
- This builder for chaining.
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hasProbingPeriodAtRoot
public boolean hasProbingPeriodAtRoot()If set at zero (the default), it is disabled. Otherwise the solver attempts probing at every 'probing_period' root node. Period of 1 enables probing at every root node.
optional int64 probing_period_at_root = 142 [default = 0];- Specified by:
hasProbingPeriodAtRootin interfaceSatParametersOrBuilder- Returns:
- Whether the probingPeriodAtRoot field is set.
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getProbingPeriodAtRoot
public long getProbingPeriodAtRoot()If set at zero (the default), it is disabled. Otherwise the solver attempts probing at every 'probing_period' root node. Period of 1 enables probing at every root node.
optional int64 probing_period_at_root = 142 [default = 0];- Specified by:
getProbingPeriodAtRootin interfaceSatParametersOrBuilder- Returns:
- The probingPeriodAtRoot.
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setProbingPeriodAtRoot
If set at zero (the default), it is disabled. Otherwise the solver attempts probing at every 'probing_period' root node. Period of 1 enables probing at every root node.
optional int64 probing_period_at_root = 142 [default = 0];- Parameters:
value- The probingPeriodAtRoot to set.- Returns:
- This builder for chaining.
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clearProbingPeriodAtRoot
If set at zero (the default), it is disabled. Otherwise the solver attempts probing at every 'probing_period' root node. Period of 1 enables probing at every root node.
optional int64 probing_period_at_root = 142 [default = 0];- Returns:
- This builder for chaining.
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hasUseProbingSearch
public boolean hasUseProbingSearch()If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Specified by:
hasUseProbingSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the useProbingSearch field is set.
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getUseProbingSearch
public boolean getUseProbingSearch()If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Specified by:
getUseProbingSearchin interfaceSatParametersOrBuilder- Returns:
- The useProbingSearch.
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setUseProbingSearch
If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Parameters:
value- The useProbingSearch to set.- Returns:
- This builder for chaining.
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clearUseProbingSearch
If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Returns:
- This builder for chaining.
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hasUseShavingInProbingSearch
public boolean hasUseShavingInProbingSearch()Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.
optional bool use_shaving_in_probing_search = 204 [default = true];- Specified by:
hasUseShavingInProbingSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the useShavingInProbingSearch field is set.
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getUseShavingInProbingSearch
public boolean getUseShavingInProbingSearch()Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.
optional bool use_shaving_in_probing_search = 204 [default = true];- Specified by:
getUseShavingInProbingSearchin interfaceSatParametersOrBuilder- Returns:
- The useShavingInProbingSearch.
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setUseShavingInProbingSearch
Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.
optional bool use_shaving_in_probing_search = 204 [default = true];- Parameters:
value- The useShavingInProbingSearch to set.- Returns:
- This builder for chaining.
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clearUseShavingInProbingSearch
Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search.
optional bool use_shaving_in_probing_search = 204 [default = true];- Returns:
- This builder for chaining.
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hasShavingSearchDeterministicTime
public boolean hasShavingSearchDeterministicTime()Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.001];- Specified by:
hasShavingSearchDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- Whether the shavingSearchDeterministicTime field is set.
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getShavingSearchDeterministicTime
public double getShavingSearchDeterministicTime()Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.001];- Specified by:
getShavingSearchDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- The shavingSearchDeterministicTime.
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setShavingSearchDeterministicTime
Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.001];- Parameters:
value- The shavingSearchDeterministicTime to set.- Returns:
- This builder for chaining.
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clearShavingSearchDeterministicTime
Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.001];- Returns:
- This builder for chaining.
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hasPseudoCostReliabilityThreshold
public boolean hasPseudoCostReliabilityThreshold()The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Specified by:
hasPseudoCostReliabilityThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the pseudoCostReliabilityThreshold field is set.
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getPseudoCostReliabilityThreshold
public long getPseudoCostReliabilityThreshold()The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Specified by:
getPseudoCostReliabilityThresholdin interfaceSatParametersOrBuilder- Returns:
- The pseudoCostReliabilityThreshold.
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setPseudoCostReliabilityThreshold
The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Parameters:
value- The pseudoCostReliabilityThreshold to set.- Returns:
- This builder for chaining.
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clearPseudoCostReliabilityThreshold
The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Returns:
- This builder for chaining.
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hasOptimizeWithCore
public boolean hasOptimizeWithCore()The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Specified by:
hasOptimizeWithCorein interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithCore field is set.
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getOptimizeWithCore
public boolean getOptimizeWithCore()The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Specified by:
getOptimizeWithCorein interfaceSatParametersOrBuilder- Returns:
- The optimizeWithCore.
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setOptimizeWithCore
The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Parameters:
value- The optimizeWithCore to set.- Returns:
- This builder for chaining.
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clearOptimizeWithCore
The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Returns:
- This builder for chaining.
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hasOptimizeWithLbTreeSearch
public boolean hasOptimizeWithLbTreeSearch()Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Specified by:
hasOptimizeWithLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithLbTreeSearch field is set.
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getOptimizeWithLbTreeSearch
public boolean getOptimizeWithLbTreeSearch()Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Specified by:
getOptimizeWithLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- The optimizeWithLbTreeSearch.
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setOptimizeWithLbTreeSearch
Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Parameters:
value- The optimizeWithLbTreeSearch to set.- Returns:
- This builder for chaining.
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clearOptimizeWithLbTreeSearch
Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Returns:
- This builder for chaining.
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hasBinarySearchNumConflicts
public boolean hasBinarySearchNumConflicts()If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Specified by:
hasBinarySearchNumConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the binarySearchNumConflicts field is set.
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getBinarySearchNumConflicts
public int getBinarySearchNumConflicts()If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Specified by:
getBinarySearchNumConflictsin interfaceSatParametersOrBuilder- Returns:
- The binarySearchNumConflicts.
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setBinarySearchNumConflicts
If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Parameters:
value- The binarySearchNumConflicts to set.- Returns:
- This builder for chaining.
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clearBinarySearchNumConflicts
If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Returns:
- This builder for chaining.
-
hasOptimizeWithMaxHs
public boolean hasOptimizeWithMaxHs()This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Specified by:
hasOptimizeWithMaxHsin interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithMaxHs field is set.
-
getOptimizeWithMaxHs
public boolean getOptimizeWithMaxHs()This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Specified by:
getOptimizeWithMaxHsin interfaceSatParametersOrBuilder- Returns:
- The optimizeWithMaxHs.
-
setOptimizeWithMaxHs
This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Parameters:
value- The optimizeWithMaxHs to set.- Returns:
- This builder for chaining.
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clearOptimizeWithMaxHs
This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Returns:
- This builder for chaining.
-
hasEnumerateAllSolutions
public boolean hasEnumerateAllSolutions()Whether we enumerate all solutions of a problem without objective. Note that setting this to true automatically disable some presolve reduction that can remove feasible solution. That is it has the same effect as setting keep_all_feasible_solutions_in_presolve. TODO(user): Do not do that and let the user choose what behavior is best by setting keep_all_feasible_solutions_in_presolve ?
optional bool enumerate_all_solutions = 87 [default = false];- Specified by:
hasEnumerateAllSolutionsin interfaceSatParametersOrBuilder- Returns:
- Whether the enumerateAllSolutions field is set.
-
getEnumerateAllSolutions
public boolean getEnumerateAllSolutions()Whether we enumerate all solutions of a problem without objective. Note that setting this to true automatically disable some presolve reduction that can remove feasible solution. That is it has the same effect as setting keep_all_feasible_solutions_in_presolve. TODO(user): Do not do that and let the user choose what behavior is best by setting keep_all_feasible_solutions_in_presolve ?
optional bool enumerate_all_solutions = 87 [default = false];- Specified by:
getEnumerateAllSolutionsin interfaceSatParametersOrBuilder- Returns:
- The enumerateAllSolutions.
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setEnumerateAllSolutions
Whether we enumerate all solutions of a problem without objective. Note that setting this to true automatically disable some presolve reduction that can remove feasible solution. That is it has the same effect as setting keep_all_feasible_solutions_in_presolve. TODO(user): Do not do that and let the user choose what behavior is best by setting keep_all_feasible_solutions_in_presolve ?
optional bool enumerate_all_solutions = 87 [default = false];- Parameters:
value- The enumerateAllSolutions to set.- Returns:
- This builder for chaining.
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clearEnumerateAllSolutions
Whether we enumerate all solutions of a problem without objective. Note that setting this to true automatically disable some presolve reduction that can remove feasible solution. That is it has the same effect as setting keep_all_feasible_solutions_in_presolve. TODO(user): Do not do that and let the user choose what behavior is best by setting keep_all_feasible_solutions_in_presolve ?
optional bool enumerate_all_solutions = 87 [default = false];- Returns:
- This builder for chaining.
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hasKeepAllFeasibleSolutionsInPresolve
public boolean hasKeepAllFeasibleSolutionsInPresolve()If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Specified by:
hasKeepAllFeasibleSolutionsInPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the keepAllFeasibleSolutionsInPresolve field is set.
-
getKeepAllFeasibleSolutionsInPresolve
public boolean getKeepAllFeasibleSolutionsInPresolve()If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Specified by:
getKeepAllFeasibleSolutionsInPresolvein interfaceSatParametersOrBuilder- Returns:
- The keepAllFeasibleSolutionsInPresolve.
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setKeepAllFeasibleSolutionsInPresolve
If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Parameters:
value- The keepAllFeasibleSolutionsInPresolve to set.- Returns:
- This builder for chaining.
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clearKeepAllFeasibleSolutionsInPresolve
If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Returns:
- This builder for chaining.
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hasFillTightenedDomainsInResponse
public boolean hasFillTightenedDomainsInResponse()If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Specified by:
hasFillTightenedDomainsInResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the fillTightenedDomainsInResponse field is set.
-
getFillTightenedDomainsInResponse
public boolean getFillTightenedDomainsInResponse()If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Specified by:
getFillTightenedDomainsInResponsein interfaceSatParametersOrBuilder- Returns:
- The fillTightenedDomainsInResponse.
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setFillTightenedDomainsInResponse
If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Parameters:
value- The fillTightenedDomainsInResponse to set.- Returns:
- This builder for chaining.
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clearFillTightenedDomainsInResponse
If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Returns:
- This builder for chaining.
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hasFillAdditionalSolutionsInResponse
public boolean hasFillAdditionalSolutionsInResponse()If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Specified by:
hasFillAdditionalSolutionsInResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the fillAdditionalSolutionsInResponse field is set.
-
getFillAdditionalSolutionsInResponse
public boolean getFillAdditionalSolutionsInResponse()If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Specified by:
getFillAdditionalSolutionsInResponsein interfaceSatParametersOrBuilder- Returns:
- The fillAdditionalSolutionsInResponse.
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setFillAdditionalSolutionsInResponse
If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Parameters:
value- The fillAdditionalSolutionsInResponse to set.- Returns:
- This builder for chaining.
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clearFillAdditionalSolutionsInResponse
If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Returns:
- This builder for chaining.
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hasInstantiateAllVariables
public boolean hasInstantiateAllVariables()If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Specified by:
hasInstantiateAllVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the instantiateAllVariables field is set.
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getInstantiateAllVariables
public boolean getInstantiateAllVariables()If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Specified by:
getInstantiateAllVariablesin interfaceSatParametersOrBuilder- Returns:
- The instantiateAllVariables.
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setInstantiateAllVariables
If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Parameters:
value- The instantiateAllVariables to set.- Returns:
- This builder for chaining.
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clearInstantiateAllVariables
If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Returns:
- This builder for chaining.
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hasAutoDetectGreaterThanAtLeastOneOf
public boolean hasAutoDetectGreaterThanAtLeastOneOf()If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Specified by:
hasAutoDetectGreaterThanAtLeastOneOfin interfaceSatParametersOrBuilder- Returns:
- Whether the autoDetectGreaterThanAtLeastOneOf field is set.
-
getAutoDetectGreaterThanAtLeastOneOf
public boolean getAutoDetectGreaterThanAtLeastOneOf()If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Specified by:
getAutoDetectGreaterThanAtLeastOneOfin interfaceSatParametersOrBuilder- Returns:
- The autoDetectGreaterThanAtLeastOneOf.
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setAutoDetectGreaterThanAtLeastOneOf
If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Parameters:
value- The autoDetectGreaterThanAtLeastOneOf to set.- Returns:
- This builder for chaining.
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clearAutoDetectGreaterThanAtLeastOneOf
If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Returns:
- This builder for chaining.
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hasStopAfterFirstSolution
public boolean hasStopAfterFirstSolution()For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Specified by:
hasStopAfterFirstSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the stopAfterFirstSolution field is set.
-
getStopAfterFirstSolution
public boolean getStopAfterFirstSolution()For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Specified by:
getStopAfterFirstSolutionin interfaceSatParametersOrBuilder- Returns:
- The stopAfterFirstSolution.
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setStopAfterFirstSolution
For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Parameters:
value- The stopAfterFirstSolution to set.- Returns:
- This builder for chaining.
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clearStopAfterFirstSolution
For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Returns:
- This builder for chaining.
-
hasStopAfterPresolve
public boolean hasStopAfterPresolve()Mainly used when improving the presolver. When true, stops the solver after the presolve is complete.
optional bool stop_after_presolve = 149 [default = false];- Specified by:
hasStopAfterPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the stopAfterPresolve field is set.
-
getStopAfterPresolve
public boolean getStopAfterPresolve()Mainly used when improving the presolver. When true, stops the solver after the presolve is complete.
optional bool stop_after_presolve = 149 [default = false];- Specified by:
getStopAfterPresolvein interfaceSatParametersOrBuilder- Returns:
- The stopAfterPresolve.
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setStopAfterPresolve
Mainly used when improving the presolver. When true, stops the solver after the presolve is complete.
optional bool stop_after_presolve = 149 [default = false];- Parameters:
value- The stopAfterPresolve to set.- Returns:
- This builder for chaining.
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clearStopAfterPresolve
Mainly used when improving the presolver. When true, stops the solver after the presolve is complete.
optional bool stop_after_presolve = 149 [default = false];- Returns:
- This builder for chaining.
-
hasUseLnsOnly
public boolean hasUseLnsOnly()LNS parameters.
optional bool use_lns_only = 101 [default = false];- Specified by:
hasUseLnsOnlyin interfaceSatParametersOrBuilder- Returns:
- Whether the useLnsOnly field is set.
-
getUseLnsOnly
public boolean getUseLnsOnly()LNS parameters.
optional bool use_lns_only = 101 [default = false];- Specified by:
getUseLnsOnlyin interfaceSatParametersOrBuilder- Returns:
- The useLnsOnly.
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setUseLnsOnly
LNS parameters.
optional bool use_lns_only = 101 [default = false];- Parameters:
value- The useLnsOnly to set.- Returns:
- This builder for chaining.
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clearUseLnsOnly
LNS parameters.
optional bool use_lns_only = 101 [default = false];- Returns:
- This builder for chaining.
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hasSolutionPoolSize
public boolean hasSolutionPoolSize()Size of the top-n different solutions kept by the solver. Currently this only impact the "base" solution chosen for a LNS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Specified by:
hasSolutionPoolSizein interfaceSatParametersOrBuilder- Returns:
- Whether the solutionPoolSize field is set.
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getSolutionPoolSize
public int getSolutionPoolSize()Size of the top-n different solutions kept by the solver. Currently this only impact the "base" solution chosen for a LNS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Specified by:
getSolutionPoolSizein interfaceSatParametersOrBuilder- Returns:
- The solutionPoolSize.
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setSolutionPoolSize
Size of the top-n different solutions kept by the solver. Currently this only impact the "base" solution chosen for a LNS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Parameters:
value- The solutionPoolSize to set.- Returns:
- This builder for chaining.
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clearSolutionPoolSize
Size of the top-n different solutions kept by the solver. Currently this only impact the "base" solution chosen for a LNS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Returns:
- This builder for chaining.
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hasUseRinsLns
public boolean hasUseRinsLns()Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Specified by:
hasUseRinsLnsin interfaceSatParametersOrBuilder- Returns:
- Whether the useRinsLns field is set.
-
getUseRinsLns
public boolean getUseRinsLns()Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Specified by:
getUseRinsLnsin interfaceSatParametersOrBuilder- Returns:
- The useRinsLns.
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setUseRinsLns
Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Parameters:
value- The useRinsLns to set.- Returns:
- This builder for chaining.
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clearUseRinsLns
Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Returns:
- This builder for chaining.
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hasUseFeasibilityPump
public boolean hasUseFeasibilityPump()Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Specified by:
hasUseFeasibilityPumpin interfaceSatParametersOrBuilder- Returns:
- Whether the useFeasibilityPump field is set.
-
getUseFeasibilityPump
public boolean getUseFeasibilityPump()Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Specified by:
getUseFeasibilityPumpin interfaceSatParametersOrBuilder- Returns:
- The useFeasibilityPump.
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setUseFeasibilityPump
Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Parameters:
value- The useFeasibilityPump to set.- Returns:
- This builder for chaining.
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clearUseFeasibilityPump
Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Returns:
- This builder for chaining.
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hasFpRounding
public boolean hasFpRounding()optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Specified by:
hasFpRoundingin interfaceSatParametersOrBuilder- Returns:
- Whether the fpRounding field is set.
-
getFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Specified by:
getFpRoundingin interfaceSatParametersOrBuilder- Returns:
- The fpRounding.
-
setFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Parameters:
value- The fpRounding to set.- Returns:
- This builder for chaining.
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clearFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Returns:
- This builder for chaining.
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hasUseRelaxationLns
public boolean hasUseRelaxationLns()Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.
optional bool use_relaxation_lns = 150 [default = false];- Specified by:
hasUseRelaxationLnsin interfaceSatParametersOrBuilder- Returns:
- Whether the useRelaxationLns field is set.
-
getUseRelaxationLns
public boolean getUseRelaxationLns()Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.
optional bool use_relaxation_lns = 150 [default = false];- Specified by:
getUseRelaxationLnsin interfaceSatParametersOrBuilder- Returns:
- The useRelaxationLns.
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setUseRelaxationLns
Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.
optional bool use_relaxation_lns = 150 [default = false];- Parameters:
value- The useRelaxationLns to set.- Returns:
- This builder for chaining.
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clearUseRelaxationLns
Turns on a lns worker which solves relaxed version of the original problem by removing constraints from the problem in order to get better bounds.
optional bool use_relaxation_lns = 150 [default = false];- Returns:
- This builder for chaining.
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hasDiversifyLnsParams
public boolean hasDiversifyLnsParams()If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Specified by:
hasDiversifyLnsParamsin interfaceSatParametersOrBuilder- Returns:
- Whether the diversifyLnsParams field is set.
-
getDiversifyLnsParams
public boolean getDiversifyLnsParams()If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Specified by:
getDiversifyLnsParamsin interfaceSatParametersOrBuilder- Returns:
- The diversifyLnsParams.
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setDiversifyLnsParams
If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Parameters:
value- The diversifyLnsParams to set.- Returns:
- This builder for chaining.
-
clearDiversifyLnsParams
If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Returns:
- This builder for chaining.
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hasRandomizeSearch
public boolean hasRandomizeSearch()Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Specified by:
hasRandomizeSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the randomizeSearch field is set.
-
getRandomizeSearch
public boolean getRandomizeSearch()Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Specified by:
getRandomizeSearchin interfaceSatParametersOrBuilder- Returns:
- The randomizeSearch.
-
setRandomizeSearch
Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Parameters:
value- The randomizeSearch to set.- Returns:
- This builder for chaining.
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clearRandomizeSearch
Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Returns:
- This builder for chaining.
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hasSearchRandomizationTolerance
public boolean hasSearchRandomizationTolerance()Search randomization will collect equivalent 'max valued' variables, and pick one randomly. For instance, if the variable strategy is CHOOSE_FIRST, all unassigned variables are equivalent. If the variable strategy is CHOOSE_LOWEST_MIN, and `lm` is the current lowest min of all unassigned variables, then the set of max valued variables will be all unassigned variables where lm <= variable min <= lm + search_randomization_toleranceoptional int64 search_randomization_tolerance = 104 [default = 0];- Specified by:
hasSearchRandomizationTolerancein interfaceSatParametersOrBuilder- Returns:
- Whether the searchRandomizationTolerance field is set.
-
getSearchRandomizationTolerance
public long getSearchRandomizationTolerance()Search randomization will collect equivalent 'max valued' variables, and pick one randomly. For instance, if the variable strategy is CHOOSE_FIRST, all unassigned variables are equivalent. If the variable strategy is CHOOSE_LOWEST_MIN, and `lm` is the current lowest min of all unassigned variables, then the set of max valued variables will be all unassigned variables where lm <= variable min <= lm + search_randomization_toleranceoptional int64 search_randomization_tolerance = 104 [default = 0];- Specified by:
getSearchRandomizationTolerancein interfaceSatParametersOrBuilder- Returns:
- The searchRandomizationTolerance.
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setSearchRandomizationTolerance
Search randomization will collect equivalent 'max valued' variables, and pick one randomly. For instance, if the variable strategy is CHOOSE_FIRST, all unassigned variables are equivalent. If the variable strategy is CHOOSE_LOWEST_MIN, and `lm` is the current lowest min of all unassigned variables, then the set of max valued variables will be all unassigned variables where lm <= variable min <= lm + search_randomization_toleranceoptional int64 search_randomization_tolerance = 104 [default = 0];- Parameters:
value- The searchRandomizationTolerance to set.- Returns:
- This builder for chaining.
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clearSearchRandomizationTolerance
Search randomization will collect equivalent 'max valued' variables, and pick one randomly. For instance, if the variable strategy is CHOOSE_FIRST, all unassigned variables are equivalent. If the variable strategy is CHOOSE_LOWEST_MIN, and `lm` is the current lowest min of all unassigned variables, then the set of max valued variables will be all unassigned variables where lm <= variable min <= lm + search_randomization_toleranceoptional int64 search_randomization_tolerance = 104 [default = 0];- Returns:
- This builder for chaining.
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hasUseOptionalVariables
public boolean hasUseOptionalVariables()If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation.
optional bool use_optional_variables = 108 [default = true];- Specified by:
hasUseOptionalVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the useOptionalVariables field is set.
-
getUseOptionalVariables
public boolean getUseOptionalVariables()If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation.
optional bool use_optional_variables = 108 [default = true];- Specified by:
getUseOptionalVariablesin interfaceSatParametersOrBuilder- Returns:
- The useOptionalVariables.
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setUseOptionalVariables
If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation.
optional bool use_optional_variables = 108 [default = true];- Parameters:
value- The useOptionalVariables to set.- Returns:
- This builder for chaining.
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clearUseOptionalVariables
If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation.
optional bool use_optional_variables = 108 [default = true];- Returns:
- This builder for chaining.
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hasUseExactLpReason
public boolean hasUseExactLpReason()The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Specified by:
hasUseExactLpReasonin interfaceSatParametersOrBuilder- Returns:
- Whether the useExactLpReason field is set.
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getUseExactLpReason
public boolean getUseExactLpReason()The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Specified by:
getUseExactLpReasonin interfaceSatParametersOrBuilder- Returns:
- The useExactLpReason.
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setUseExactLpReason
The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Parameters:
value- The useExactLpReason to set.- Returns:
- This builder for chaining.
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clearUseExactLpReason
The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Returns:
- This builder for chaining.
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hasUseBranchingInLp
public boolean hasUseBranchingInLp()If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.
optional bool use_branching_in_lp = 139 [default = false];- Specified by:
hasUseBranchingInLpin interfaceSatParametersOrBuilder- Returns:
- Whether the useBranchingInLp field is set.
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getUseBranchingInLp
public boolean getUseBranchingInLp()If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.
optional bool use_branching_in_lp = 139 [default = false];- Specified by:
getUseBranchingInLpin interfaceSatParametersOrBuilder- Returns:
- The useBranchingInLp.
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setUseBranchingInLp
If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.
optional bool use_branching_in_lp = 139 [default = false];- Parameters:
value- The useBranchingInLp to set.- Returns:
- This builder for chaining.
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clearUseBranchingInLp
If true, the solver attemts to generate more info inside lp propagator by branching on some variables if certain criteria are met during the search tree exploration.
optional bool use_branching_in_lp = 139 [default = false];- Returns:
- This builder for chaining.
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hasUseCombinedNoOverlap
public boolean hasUseCombinedNoOverlap()This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Specified by:
hasUseCombinedNoOverlapin interfaceSatParametersOrBuilder- Returns:
- Whether the useCombinedNoOverlap field is set.
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getUseCombinedNoOverlap
public boolean getUseCombinedNoOverlap()This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Specified by:
getUseCombinedNoOverlapin interfaceSatParametersOrBuilder- Returns:
- The useCombinedNoOverlap.
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setUseCombinedNoOverlap
This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Parameters:
value- The useCombinedNoOverlap to set.- Returns:
- This builder for chaining.
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clearUseCombinedNoOverlap
This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Returns:
- This builder for chaining.
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hasCatchSigintSignal
public boolean hasCatchSigintSignal()Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Specified by:
hasCatchSigintSignalin interfaceSatParametersOrBuilder- Returns:
- Whether the catchSigintSignal field is set.
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getCatchSigintSignal
public boolean getCatchSigintSignal()Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Specified by:
getCatchSigintSignalin interfaceSatParametersOrBuilder- Returns:
- The catchSigintSignal.
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setCatchSigintSignal
Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Parameters:
value- The catchSigintSignal to set.- Returns:
- This builder for chaining.
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clearCatchSigintSignal
Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Returns:
- This builder for chaining.
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hasUseImpliedBounds
public boolean hasUseImpliedBounds()Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Specified by:
hasUseImpliedBoundsin interfaceSatParametersOrBuilder- Returns:
- Whether the useImpliedBounds field is set.
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getUseImpliedBounds
public boolean getUseImpliedBounds()Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Specified by:
getUseImpliedBoundsin interfaceSatParametersOrBuilder- Returns:
- The useImpliedBounds.
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setUseImpliedBounds
Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Parameters:
value- The useImpliedBounds to set.- Returns:
- This builder for chaining.
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clearUseImpliedBounds
Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Returns:
- This builder for chaining.
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hasPolishLpSolution
public boolean hasPolishLpSolution()Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Specified by:
hasPolishLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the polishLpSolution field is set.
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getPolishLpSolution
public boolean getPolishLpSolution()Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Specified by:
getPolishLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The polishLpSolution.
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setPolishLpSolution
Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Parameters:
value- The polishLpSolution to set.- Returns:
- This builder for chaining.
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clearPolishLpSolution
Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Returns:
- This builder for chaining.
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hasConvertIntervals
public boolean hasConvertIntervals()Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Specified by:
hasConvertIntervalsin interfaceSatParametersOrBuilder- Returns:
- Whether the convertIntervals field is set.
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getConvertIntervals
public boolean getConvertIntervals()Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Specified by:
getConvertIntervalsin interfaceSatParametersOrBuilder- Returns:
- The convertIntervals.
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setConvertIntervals
Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Parameters:
value- The convertIntervals to set.- Returns:
- This builder for chaining.
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clearConvertIntervals
Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Returns:
- This builder for chaining.
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hasSymmetryLevel
public boolean hasSymmetryLevel()Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search.
optional int32 symmetry_level = 183 [default = 2];- Specified by:
hasSymmetryLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the symmetryLevel field is set.
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getSymmetryLevel
public int getSymmetryLevel()Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search.
optional int32 symmetry_level = 183 [default = 2];- Specified by:
getSymmetryLevelin interfaceSatParametersOrBuilder- Returns:
- The symmetryLevel.
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setSymmetryLevel
Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search.
optional int32 symmetry_level = 183 [default = 2];- Parameters:
value- The symmetryLevel to set.- Returns:
- This builder for chaining.
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clearSymmetryLevel
Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search.
optional int32 symmetry_level = 183 [default = 2];- Returns:
- This builder for chaining.
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hasMipMaxBound
public boolean hasMipMaxBound()We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Specified by:
hasMipMaxBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxBound field is set.
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getMipMaxBound
public double getMipMaxBound()We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Specified by:
getMipMaxBoundin interfaceSatParametersOrBuilder- Returns:
- The mipMaxBound.
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setMipMaxBound
We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Parameters:
value- The mipMaxBound to set.- Returns:
- This builder for chaining.
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clearMipMaxBound
We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Returns:
- This builder for chaining.
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hasMipVarScaling
public boolean hasMipVarScaling()All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Specified by:
hasMipVarScalingin interfaceSatParametersOrBuilder- Returns:
- Whether the mipVarScaling field is set.
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getMipVarScaling
public double getMipVarScaling()All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Specified by:
getMipVarScalingin interfaceSatParametersOrBuilder- Returns:
- The mipVarScaling.
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setMipVarScaling
All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Parameters:
value- The mipVarScaling to set.- Returns:
- This builder for chaining.
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clearMipVarScaling
All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Returns:
- This builder for chaining.
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hasMipAutomaticallyScaleVariables
public boolean hasMipAutomaticallyScaleVariables()If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Specified by:
hasMipAutomaticallyScaleVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the mipAutomaticallyScaleVariables field is set.
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getMipAutomaticallyScaleVariables
public boolean getMipAutomaticallyScaleVariables()If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Specified by:
getMipAutomaticallyScaleVariablesin interfaceSatParametersOrBuilder- Returns:
- The mipAutomaticallyScaleVariables.
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setMipAutomaticallyScaleVariables
If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Parameters:
value- The mipAutomaticallyScaleVariables to set.- Returns:
- This builder for chaining.
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clearMipAutomaticallyScaleVariables
If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Returns:
- This builder for chaining.
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hasOnlySolveIp
public boolean hasOnlySolveIp()If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Specified by:
hasOnlySolveIpin interfaceSatParametersOrBuilder- Returns:
- Whether the onlySolveIp field is set.
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getOnlySolveIp
public boolean getOnlySolveIp()If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Specified by:
getOnlySolveIpin interfaceSatParametersOrBuilder- Returns:
- The onlySolveIp.
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setOnlySolveIp
If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Parameters:
value- The onlySolveIp to set.- Returns:
- This builder for chaining.
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clearOnlySolveIp
If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Returns:
- This builder for chaining.
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hasMipWantedPrecision
public boolean hasMipWantedPrecision()When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Specified by:
hasMipWantedPrecisionin interfaceSatParametersOrBuilder- Returns:
- Whether the mipWantedPrecision field is set.
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getMipWantedPrecision
public double getMipWantedPrecision()When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Specified by:
getMipWantedPrecisionin interfaceSatParametersOrBuilder- Returns:
- The mipWantedPrecision.
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setMipWantedPrecision
When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Parameters:
value- The mipWantedPrecision to set.- Returns:
- This builder for chaining.
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clearMipWantedPrecision
When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Returns:
- This builder for chaining.
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hasMipMaxActivityExponent
public boolean hasMipMaxActivityExponent()To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Specified by:
hasMipMaxActivityExponentin interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxActivityExponent field is set.
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getMipMaxActivityExponent
public int getMipMaxActivityExponent()To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Specified by:
getMipMaxActivityExponentin interfaceSatParametersOrBuilder- Returns:
- The mipMaxActivityExponent.
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setMipMaxActivityExponent
To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Parameters:
value- The mipMaxActivityExponent to set.- Returns:
- This builder for chaining.
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clearMipMaxActivityExponent
To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Returns:
- This builder for chaining.
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hasMipCheckPrecision
public boolean hasMipCheckPrecision()As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Specified by:
hasMipCheckPrecisionin interfaceSatParametersOrBuilder- Returns:
- Whether the mipCheckPrecision field is set.
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getMipCheckPrecision
public double getMipCheckPrecision()As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Specified by:
getMipCheckPrecisionin interfaceSatParametersOrBuilder- Returns:
- The mipCheckPrecision.
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setMipCheckPrecision
As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Parameters:
value- The mipCheckPrecision to set.- Returns:
- This builder for chaining.
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clearMipCheckPrecision
As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Returns:
- This builder for chaining.
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hasMipComputeTrueObjectiveBound
public boolean hasMipComputeTrueObjectiveBound()Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Specified by:
hasMipComputeTrueObjectiveBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the mipComputeTrueObjectiveBound field is set.
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getMipComputeTrueObjectiveBound
public boolean getMipComputeTrueObjectiveBound()Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Specified by:
getMipComputeTrueObjectiveBoundin interfaceSatParametersOrBuilder- Returns:
- The mipComputeTrueObjectiveBound.
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setMipComputeTrueObjectiveBound
Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Parameters:
value- The mipComputeTrueObjectiveBound to set.- Returns:
- This builder for chaining.
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clearMipComputeTrueObjectiveBound
Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Returns:
- This builder for chaining.
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hasMipMaxValidMagnitude
public boolean hasMipMaxValidMagnitude()Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+30];- Specified by:
hasMipMaxValidMagnitudein interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxValidMagnitude field is set.
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getMipMaxValidMagnitude
public double getMipMaxValidMagnitude()Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+30];- Specified by:
getMipMaxValidMagnitudein interfaceSatParametersOrBuilder- Returns:
- The mipMaxValidMagnitude.
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setMipMaxValidMagnitude
Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+30];- Parameters:
value- The mipMaxValidMagnitude to set.- Returns:
- This builder for chaining.
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clearMipMaxValidMagnitude
Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+30];- Returns:
- This builder for chaining.
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setUnknownFields
public final SatParameters.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) - Specified by:
setUnknownFieldsin interfacecom.google.protobuf.Message.Builder- Overrides:
setUnknownFieldsin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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mergeUnknownFields
public final SatParameters.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) - Specified by:
mergeUnknownFieldsin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeUnknownFieldsin classcom.google.protobuf.GeneratedMessageV3.Builder<SatParameters.Builder>
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