Uses of Class
operations_research.pdlp.Solvers.PrimalDualHybridGradientParams.Builder
Packages that use Solvers.PrimalDualHybridGradientParams.Builder
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Uses of Solvers.PrimalDualHybridGradientParams.Builder in operations_research.pdlp
Methods in operations_research.pdlp that return Solvers.PrimalDualHybridGradientParams.BuilderModifier and TypeMethodDescriptionSolvers.PrimalDualHybridGradientParams.Builder.addAllRandomProjectionSeeds(Iterable<? extends Integer> values) Seeds for generating (pseudo-)random projections of iterates during termination checks.Solvers.PrimalDualHybridGradientParams.Builder.addRandomProjectionSeeds(int value) Seeds for generating (pseudo-)random projections of iterates during termination checks.Solvers.PrimalDualHybridGradientParams.Builder.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) Solvers.PrimalDualHybridGradientParams.Builder.clear()Solvers.PrimalDualHybridGradientParams.Builder.clearAdaptiveLinesearchParameters()optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;Solvers.PrimalDualHybridGradientParams.Builder.clearDiagonalQpTrustRegionSolverTolerance()The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter.Solvers.PrimalDualHybridGradientParams.Builder.clearField(com.google.protobuf.Descriptors.FieldDescriptor field) Solvers.PrimalDualHybridGradientParams.Builder.clearInfiniteConstraintBoundThreshold()When computing relative feasibility norms, constraint bounds with absolute value at least this threshold are treated as infinite, and hence not included in the relative feasibility norm.Solvers.PrimalDualHybridGradientParams.Builder.clearInitialPrimalWeight()The initial value of the primal weight (i.e., the ratio of primal and dual step sizes).Solvers.PrimalDualHybridGradientParams.Builder.clearInitialStepSizeScaling()Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).Solvers.PrimalDualHybridGradientParams.Builder.clearL2NormRescaling()If true, applies L_2 norm rescaling after the Ruiz rescaling.Solvers.PrimalDualHybridGradientParams.Builder.clearLinesearchRule()Linesearch rule applied at each major iteration.Solvers.PrimalDualHybridGradientParams.Builder.clearLInfRuizIterations()Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix.Solvers.PrimalDualHybridGradientParams.Builder.clearMajorIterationFrequency()The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight.Solvers.PrimalDualHybridGradientParams.Builder.clearMalitskyPockParameters()optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;Solvers.PrimalDualHybridGradientParams.Builder.clearNecessaryReductionForRestart()For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse.Solvers.PrimalDualHybridGradientParams.Builder.clearNumShards()For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards.Solvers.PrimalDualHybridGradientParams.Builder.clearNumThreads()The number of threads to use.Solvers.PrimalDualHybridGradientParams.Builder.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) Solvers.PrimalDualHybridGradientParams.Builder.clearPresolveOptions()optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;Solvers.PrimalDualHybridGradientParams.Builder.clearPrimalWeightUpdateSmoothing()This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted).Solvers.PrimalDualHybridGradientParams.Builder.clearRandomProjectionSeeds()Seeds for generating (pseudo-)random projections of iterates during termination checks.Solvers.PrimalDualHybridGradientParams.Builder.clearRecordIterationStats()If true, the iteration_stats field of the SolveLog output will be populated at every iteration.Solvers.PrimalDualHybridGradientParams.Builder.clearRestartStrategy()NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.Solvers.PrimalDualHybridGradientParams.Builder.clearSufficientReductionForRestart()For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart.Solvers.PrimalDualHybridGradientParams.Builder.clearTerminationCheckFrequency()The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats.Solvers.PrimalDualHybridGradientParams.Builder.clearTerminationCriteria()optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;Solvers.PrimalDualHybridGradientParams.Builder.clearUseDiagonalQpTrustRegionSolver()When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term.Solvers.PrimalDualHybridGradientParams.Builder.clearVerbosityLevel()The verbosity of logging.Solvers.PrimalDualHybridGradientParams.Builder.clone()SolveLogOuterClass.SolveLog.Builder.getParamsBuilder()If solved with PDLP, the parameters for this solve.Solvers.PrimalDualHybridGradientParams.Builder.mergeAdaptiveLinesearchParameters(Solvers.AdaptiveLinesearchParams value) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;Solvers.PrimalDualHybridGradientParams.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) Solvers.PrimalDualHybridGradientParams.Builder.mergeFrom(com.google.protobuf.Message other) Solvers.PrimalDualHybridGradientParams.Builder.mergeFrom(Solvers.PrimalDualHybridGradientParams other) Solvers.PrimalDualHybridGradientParams.Builder.mergeMalitskyPockParameters(Solvers.MalitskyPockParams value) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;Solvers.PrimalDualHybridGradientParams.Builder.mergePresolveOptions(Solvers.PrimalDualHybridGradientParams.PresolveOptions value) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;Solvers.PrimalDualHybridGradientParams.Builder.mergeTerminationCriteria(Solvers.TerminationCriteria value) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;Solvers.PrimalDualHybridGradientParams.Builder.mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) Solvers.PrimalDualHybridGradientParams.newBuilder()Solvers.PrimalDualHybridGradientParams.newBuilder(Solvers.PrimalDualHybridGradientParams prototype) Solvers.PrimalDualHybridGradientParams.newBuilderForType()Solvers.PrimalDualHybridGradientParams.newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) Solvers.PrimalDualHybridGradientParams.Builder.setAdaptiveLinesearchParameters(Solvers.AdaptiveLinesearchParams value) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;Solvers.PrimalDualHybridGradientParams.Builder.setAdaptiveLinesearchParameters(Solvers.AdaptiveLinesearchParams.Builder builderForValue) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;Solvers.PrimalDualHybridGradientParams.Builder.setDiagonalQpTrustRegionSolverTolerance(double value) The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter.Solvers.PrimalDualHybridGradientParams.Builder.setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) Solvers.PrimalDualHybridGradientParams.Builder.setInfiniteConstraintBoundThreshold(double value) When computing relative feasibility norms, constraint bounds with absolute value at least this threshold are treated as infinite, and hence not included in the relative feasibility norm.Solvers.PrimalDualHybridGradientParams.Builder.setInitialPrimalWeight(double value) The initial value of the primal weight (i.e., the ratio of primal and dual step sizes).Solvers.PrimalDualHybridGradientParams.Builder.setInitialStepSizeScaling(double value) Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).Solvers.PrimalDualHybridGradientParams.Builder.setL2NormRescaling(boolean value) If true, applies L_2 norm rescaling after the Ruiz rescaling.Solvers.PrimalDualHybridGradientParams.Builder.setLinesearchRule(Solvers.PrimalDualHybridGradientParams.LinesearchRule value) Linesearch rule applied at each major iteration.Solvers.PrimalDualHybridGradientParams.Builder.setLInfRuizIterations(int value) Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix.Solvers.PrimalDualHybridGradientParams.Builder.setMajorIterationFrequency(int value) The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight.Solvers.PrimalDualHybridGradientParams.Builder.setMalitskyPockParameters(Solvers.MalitskyPockParams value) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;Solvers.PrimalDualHybridGradientParams.Builder.setMalitskyPockParameters(Solvers.MalitskyPockParams.Builder builderForValue) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;Solvers.PrimalDualHybridGradientParams.Builder.setNecessaryReductionForRestart(double value) For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse.Solvers.PrimalDualHybridGradientParams.Builder.setNumShards(int value) For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards.Solvers.PrimalDualHybridGradientParams.Builder.setNumThreads(int value) The number of threads to use.Solvers.PrimalDualHybridGradientParams.Builder.setPresolveOptions(Solvers.PrimalDualHybridGradientParams.PresolveOptions value) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;Solvers.PrimalDualHybridGradientParams.Builder.setPresolveOptions(Solvers.PrimalDualHybridGradientParams.PresolveOptions.Builder builderForValue) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;Solvers.PrimalDualHybridGradientParams.Builder.setPrimalWeightUpdateSmoothing(double value) This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted).Solvers.PrimalDualHybridGradientParams.Builder.setRandomProjectionSeeds(int index, int value) Seeds for generating (pseudo-)random projections of iterates during termination checks.Solvers.PrimalDualHybridGradientParams.Builder.setRecordIterationStats(boolean value) If true, the iteration_stats field of the SolveLog output will be populated at every iteration.Solvers.PrimalDualHybridGradientParams.Builder.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) Solvers.PrimalDualHybridGradientParams.Builder.setRestartStrategy(Solvers.PrimalDualHybridGradientParams.RestartStrategy value) NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.Solvers.PrimalDualHybridGradientParams.Builder.setSufficientReductionForRestart(double value) For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart.Solvers.PrimalDualHybridGradientParams.Builder.setTerminationCheckFrequency(int value) The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats.Solvers.PrimalDualHybridGradientParams.Builder.setTerminationCriteria(Solvers.TerminationCriteria value) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;Solvers.PrimalDualHybridGradientParams.Builder.setTerminationCriteria(Solvers.TerminationCriteria.Builder builderForValue) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;Solvers.PrimalDualHybridGradientParams.Builder.setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) Solvers.PrimalDualHybridGradientParams.Builder.setUseDiagonalQpTrustRegionSolver(boolean value) When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term.Solvers.PrimalDualHybridGradientParams.Builder.setVerbosityLevel(int value) The verbosity of logging.Solvers.PrimalDualHybridGradientParams.toBuilder()Methods in operations_research.pdlp with parameters of type Solvers.PrimalDualHybridGradientParams.BuilderModifier and TypeMethodDescriptionSolveLogOuterClass.SolveLog.Builder.setParams(Solvers.PrimalDualHybridGradientParams.Builder builderForValue) If solved with PDLP, the parameters for this solve.