Package com.google.ortools.sat

Class CpSolverResponse.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderType>
com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>
com.google.ortools.sat.CpSolverResponse.Builder
All Implemented Interfaces:
CpSolverResponseOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, java.lang.Cloneable
Enclosing class:
CpSolverResponse
public static final class CpSolverResponse.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>
implements CpSolverResponseOrBuilder
 The response returned by a solver trying to solve a CpModelProto.
 TODO(user): support returning multiple solutions. Look at the Stubby
 streaming API as we probably wants to get them as they are found.
 Next id: 27
Protobuf type operations_research.sat.CpSolverResponse

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • clear

      public CpSolverResponse.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • getDefaultInstanceForType

      public CpSolverResponse getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public CpSolverResponse build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public CpSolverResponse buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • clone

      public CpSolverResponse.Builder clone()
      Specified by:
      clone in interface com.google.protobuf.Message.Builder
      Specified by:
      clone in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clone in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • setField

      public CpSolverResponse.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)
      Specified by:
      setField in interface com.google.protobuf.Message.Builder
      Overrides:
      setField in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • clearField

      public CpSolverResponse.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
      Specified by:
      clearField in interface com.google.protobuf.Message.Builder
      Overrides:
      clearField in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • clearOneof

      public CpSolverResponse.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
      Specified by:
      clearOneof in interface com.google.protobuf.Message.Builder
      Overrides:
      clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • setRepeatedField

      public CpSolverResponse.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value)
      Specified by:
      setRepeatedField in interface com.google.protobuf.Message.Builder
      Overrides:
      setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • addRepeatedField

      public CpSolverResponse.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)
      Specified by:
      addRepeatedField in interface com.google.protobuf.Message.Builder
      Overrides:
      addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • mergeFrom

      public CpSolverResponse.Builder mergeFrom​(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<CpSolverResponse.Builder>

    • mergeFrom

      public CpSolverResponse.Builder mergeFrom​(CpSolverResponse other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • mergeFrom

      public CpSolverResponse.Builder mergeFrom​(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<CpSolverResponse.Builder>
      Throws:
      java.io.IOException

    • getStatusValue

      public int getStatusValue()
       The status of the solve.
      .operations_research.sat.CpSolverStatus status = 1;
      Specified by:
      getStatusValue in interface CpSolverResponseOrBuilder
      Returns:
      The enum numeric value on the wire for status.

    • setStatusValue

      public CpSolverResponse.Builder setStatusValue​(int value)
       The status of the solve.
      .operations_research.sat.CpSolverStatus status = 1;
      Parameters:
      value - The enum numeric value on the wire for status to set.
      Returns:
      This builder for chaining.

    • getStatus

      public CpSolverStatus getStatus()
       The status of the solve.
      .operations_research.sat.CpSolverStatus status = 1;
      Specified by:
      getStatus in interface CpSolverResponseOrBuilder
      Returns:
      The status.

    • setStatus

      public CpSolverResponse.Builder setStatus​(CpSolverStatus value)
       The status of the solve.
      .operations_research.sat.CpSolverStatus status = 1;
      Parameters:
      value - The status to set.
      Returns:
      This builder for chaining.

    • clearStatus

      public CpSolverResponse.Builder clearStatus()
       The status of the solve.
      .operations_research.sat.CpSolverStatus status = 1;
      Returns:
      This builder for chaining.

    • getSolutionList

      public java.util.List<java.lang.Long> getSolutionList()
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Specified by:
      getSolutionList in interface CpSolverResponseOrBuilder
      Returns:
      A list containing the solution.

    • getSolutionCount

      public int getSolutionCount()
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Specified by:
      getSolutionCount in interface CpSolverResponseOrBuilder
      Returns:
      The count of solution.

    • getSolution

      public long getSolution​(int index)
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Specified by:
      getSolution in interface CpSolverResponseOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The solution at the given index.

    • setSolution

      public CpSolverResponse.Builder setSolution​(int index, long value)
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Parameters:
      index - The index to set the value at.
      value - The solution to set.
      Returns:
      This builder for chaining.

    • addSolution

      public CpSolverResponse.Builder addSolution​(long value)
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Parameters:
      value - The solution to add.
      Returns:
      This builder for chaining.

    • addAllSolution

      public CpSolverResponse.Builder addAllSolution​(java.lang.Iterable<? extends java.lang.Long> values)
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Parameters:
      values - The solution to add.
      Returns:
      This builder for chaining.

    • clearSolution

      public CpSolverResponse.Builder clearSolution()
       A feasible solution to the given problem. Depending on the returned status
 it may be optimal or just feasible. This is in one-to-one correspondence
 with a CpModelProto::variables repeated field and list the values of all
 the variables.
      repeated int64 solution = 2;
      Returns:
      This builder for chaining.

    • getObjectiveValue

      public double getObjectiveValue()
       Only make sense for an optimization problem. The objective value of the
 returned solution if it is non-empty. If there is no solution, then for a
 minimization problem, this will be an upper-bound of the objective of any
 feasible solution, and a lower-bound for a maximization problem.
      double objective_value = 3;
      Specified by:
      getObjectiveValue in interface CpSolverResponseOrBuilder
      Returns:
      The objectiveValue.

    • setObjectiveValue

      public CpSolverResponse.Builder setObjectiveValue​(double value)
       Only make sense for an optimization problem. The objective value of the
 returned solution if it is non-empty. If there is no solution, then for a
 minimization problem, this will be an upper-bound of the objective of any
 feasible solution, and a lower-bound for a maximization problem.
      double objective_value = 3;
      Parameters:
      value - The objectiveValue to set.
      Returns:
      This builder for chaining.

    • clearObjectiveValue

      public CpSolverResponse.Builder clearObjectiveValue()
       Only make sense for an optimization problem. The objective value of the
 returned solution if it is non-empty. If there is no solution, then for a
 minimization problem, this will be an upper-bound of the objective of any
 feasible solution, and a lower-bound for a maximization problem.
      double objective_value = 3;
      Returns:
      This builder for chaining.

    • getBestObjectiveBound

      public double getBestObjectiveBound()
       Only make sense for an optimization problem. A proven lower-bound on the
 objective for a minimization problem, or a proven upper-bound for a
 maximization problem.
      double best_objective_bound = 4;
      Specified by:
      getBestObjectiveBound in interface CpSolverResponseOrBuilder
      Returns:
      The bestObjectiveBound.

    • setBestObjectiveBound

      public CpSolverResponse.Builder setBestObjectiveBound​(double value)
       Only make sense for an optimization problem. A proven lower-bound on the
 objective for a minimization problem, or a proven upper-bound for a
 maximization problem.
      double best_objective_bound = 4;
      Parameters:
      value - The bestObjectiveBound to set.
      Returns:
      This builder for chaining.

    • clearBestObjectiveBound

      public CpSolverResponse.Builder clearBestObjectiveBound()
       Only make sense for an optimization problem. A proven lower-bound on the
 objective for a minimization problem, or a proven upper-bound for a
 maximization problem.
      double best_objective_bound = 4;
      Returns:
      This builder for chaining.

    • getSolutionLowerBoundsList

      public java.util.List<java.lang.Long> getSolutionLowerBoundsList()
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Specified by:
      getSolutionLowerBoundsList in interface CpSolverResponseOrBuilder
      Returns:
      A list containing the solutionLowerBounds.

    • getSolutionLowerBoundsCount

      public int getSolutionLowerBoundsCount()
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Specified by:
      getSolutionLowerBoundsCount in interface CpSolverResponseOrBuilder
      Returns:
      The count of solutionLowerBounds.

    • getSolutionLowerBounds

      public long getSolutionLowerBounds​(int index)
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Specified by:
      getSolutionLowerBounds in interface CpSolverResponseOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The solutionLowerBounds at the given index.

    • setSolutionLowerBounds

      public CpSolverResponse.Builder setSolutionLowerBounds​(int index, long value)
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Parameters:
      index - The index to set the value at.
      value - The solutionLowerBounds to set.
      Returns:
      This builder for chaining.

    • addSolutionLowerBounds

      public CpSolverResponse.Builder addSolutionLowerBounds​(long value)
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Parameters:
      value - The solutionLowerBounds to add.
      Returns:
      This builder for chaining.

    • addAllSolutionLowerBounds

      public CpSolverResponse.Builder addAllSolutionLowerBounds​(java.lang.Iterable<? extends java.lang.Long> values)
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Parameters:
      values - The solutionLowerBounds to add.
      Returns:
      This builder for chaining.

    • clearSolutionLowerBounds

      public CpSolverResponse.Builder clearSolutionLowerBounds()
       Advanced usage.
 If the problem has some variables that are not fixed at the end of the
 search (because of a particular search strategy in the CpModelProto) then
 this will be used instead of filling the solution above. The two fields
 will then contains the lower and upper bounds of each variable as they were
 when the best "solution" was found.
      repeated int64 solution_lower_bounds = 18;
      Returns:
      This builder for chaining.

    • getSolutionUpperBoundsList

      public java.util.List<java.lang.Long> getSolutionUpperBoundsList()
      repeated int64 solution_upper_bounds = 19;
      Specified by:
      getSolutionUpperBoundsList in interface CpSolverResponseOrBuilder
      Returns:
      A list containing the solutionUpperBounds.

    • getSolutionUpperBoundsCount

      public int getSolutionUpperBoundsCount()
      repeated int64 solution_upper_bounds = 19;
      Specified by:
      getSolutionUpperBoundsCount in interface CpSolverResponseOrBuilder
      Returns:
      The count of solutionUpperBounds.

    • getSolutionUpperBounds

      public long getSolutionUpperBounds​(int index)
      repeated int64 solution_upper_bounds = 19;
      Specified by:
      getSolutionUpperBounds in interface CpSolverResponseOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The solutionUpperBounds at the given index.

    • setSolutionUpperBounds

      public CpSolverResponse.Builder setSolutionUpperBounds​(int index, long value)
      repeated int64 solution_upper_bounds = 19;
      Parameters:
      index - The index to set the value at.
      value - The solutionUpperBounds to set.
      Returns:
      This builder for chaining.

    • addSolutionUpperBounds

      public CpSolverResponse.Builder addSolutionUpperBounds​(long value)
      repeated int64 solution_upper_bounds = 19;
      Parameters:
      value - The solutionUpperBounds to add.
      Returns:
      This builder for chaining.

    • addAllSolutionUpperBounds

      public CpSolverResponse.Builder addAllSolutionUpperBounds​(java.lang.Iterable<? extends java.lang.Long> values)
      repeated int64 solution_upper_bounds = 19;
      Parameters:
      values - The solutionUpperBounds to add.
      Returns:
      This builder for chaining.

    • clearSolutionUpperBounds

      public CpSolverResponse.Builder clearSolutionUpperBounds()
      repeated int64 solution_upper_bounds = 19;
      Returns:
      This builder for chaining.

    • getTightenedVariablesList

      public java.util.List<IntegerVariableProto> getTightenedVariablesList()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;
      Specified by:
      getTightenedVariablesList in interface CpSolverResponseOrBuilder

    • getTightenedVariablesCount

      public int getTightenedVariablesCount()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;
      Specified by:
      getTightenedVariablesCount in interface CpSolverResponseOrBuilder

    • getTightenedVariables

      public IntegerVariableProto getTightenedVariables​(int index)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;
      Specified by:
      getTightenedVariables in interface CpSolverResponseOrBuilder

    • setTightenedVariables

      public CpSolverResponse.Builder setTightenedVariables​(int index, IntegerVariableProto value)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • setTightenedVariables

      public CpSolverResponse.Builder setTightenedVariables​(int index, IntegerVariableProto.Builder builderForValue)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addTightenedVariables

      public CpSolverResponse.Builder addTightenedVariables​(IntegerVariableProto value)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addTightenedVariables

      public CpSolverResponse.Builder addTightenedVariables​(int index, IntegerVariableProto value)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addTightenedVariables

      public CpSolverResponse.Builder addTightenedVariables​(IntegerVariableProto.Builder builderForValue)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addTightenedVariables

      public CpSolverResponse.Builder addTightenedVariables​(int index, IntegerVariableProto.Builder builderForValue)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addAllTightenedVariables

      public CpSolverResponse.Builder addAllTightenedVariables​(java.lang.Iterable<? extends IntegerVariableProto> values)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • clearTightenedVariables

      public CpSolverResponse.Builder clearTightenedVariables()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • removeTightenedVariables

      public CpSolverResponse.Builder removeTightenedVariables​(int index)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • getTightenedVariablesBuilder

      public IntegerVariableProto.Builder getTightenedVariablesBuilder​(int index)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • getTightenedVariablesOrBuilder

      public IntegerVariableProtoOrBuilder getTightenedVariablesOrBuilder​(int index)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;
      Specified by:
      getTightenedVariablesOrBuilder in interface CpSolverResponseOrBuilder

    • getTightenedVariablesOrBuilderList

      public java.util.List<? extends IntegerVariableProtoOrBuilder> getTightenedVariablesOrBuilderList()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;
      Specified by:
      getTightenedVariablesOrBuilderList in interface CpSolverResponseOrBuilder

    • addTightenedVariablesBuilder

      public IntegerVariableProto.Builder addTightenedVariablesBuilder()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • addTightenedVariablesBuilder

      public IntegerVariableProto.Builder addTightenedVariablesBuilder​(int index)
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • getTightenedVariablesBuilderList

      public java.util.List<IntegerVariableProto.Builder> getTightenedVariablesBuilderList()
       Advanced usage.
 If the option fill_tightened_domains_in_response is set, then this field
 will be a copy of the CpModelProto.variables where each domain has been
 reduced using the information the solver was able to derive. Note that this
 is only filled with the info derived during a normal search and we do not
 have any dedicated algorithm to improve it.
 If the problem is a feasibility problem, then these bounds will be valid
 for any feasible solution. If the problem is an optimization problem, then
 these bounds will only be valid for any OPTIMAL solutions, it can exclude
 sub-optimal feasible ones.
      repeated .operations_research.sat.IntegerVariableProto tightened_variables = 21;

    • getSufficientAssumptionsForInfeasibilityList

      public java.util.List<java.lang.Integer> getSufficientAssumptionsForInfeasibilityList()
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Specified by:
      getSufficientAssumptionsForInfeasibilityList in interface CpSolverResponseOrBuilder
      Returns:
      A list containing the sufficientAssumptionsForInfeasibility.

    • getSufficientAssumptionsForInfeasibilityCount

      public int getSufficientAssumptionsForInfeasibilityCount()
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Specified by:
      getSufficientAssumptionsForInfeasibilityCount in interface CpSolverResponseOrBuilder
      Returns:
      The count of sufficientAssumptionsForInfeasibility.

    • getSufficientAssumptionsForInfeasibility

      public int getSufficientAssumptionsForInfeasibility​(int index)
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Specified by:
      getSufficientAssumptionsForInfeasibility in interface CpSolverResponseOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The sufficientAssumptionsForInfeasibility at the given index.

    • setSufficientAssumptionsForInfeasibility

      public CpSolverResponse.Builder setSufficientAssumptionsForInfeasibility​(int index, int value)
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Parameters:
      index - The index to set the value at.
      value - The sufficientAssumptionsForInfeasibility to set.
      Returns:
      This builder for chaining.

    • addSufficientAssumptionsForInfeasibility

      public CpSolverResponse.Builder addSufficientAssumptionsForInfeasibility​(int value)
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Parameters:
      value - The sufficientAssumptionsForInfeasibility to add.
      Returns:
      This builder for chaining.

    • addAllSufficientAssumptionsForInfeasibility

      public CpSolverResponse.Builder addAllSufficientAssumptionsForInfeasibility​(java.lang.Iterable<? extends java.lang.Integer> values)
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Parameters:
      values - The sufficientAssumptionsForInfeasibility to add.
      Returns:
      This builder for chaining.

    • clearSufficientAssumptionsForInfeasibility

      public CpSolverResponse.Builder clearSufficientAssumptionsForInfeasibility()
       A subset of the model "assumptions" field. This will only be filled if the
 status is INFEASIBLE. This subset of assumption will be enough to still get
 an infeasible problem.
 This is related to what is called the irreducible inconsistent subsystem or
 IIS. Except one is only concerned by the provided assumptions. There is
 also no guarantee that we return an irreducible (aka minimal subset).
 However, this is based on SAT explanation and there is a good chance it is
 not too large.
 If you really want a minimal subset, a possible way to get one is by
 changing your model to minimize the number of assumptions at false, but
 this is likely an harder problem to solve.
 TODO(user): Allows for returning multiple core at once.
      repeated int32 sufficient_assumptions_for_infeasibility = 23;
      Returns:
      This builder for chaining.

    • getAllSolutionsWereFound

      public boolean getAllSolutionsWereFound()
       This will be true iff the solver was asked to find all solutions to a
 satisfiability problem (or all optimal solutions to an optimization
 problem), and it was successful in doing so.
 TODO(user): Remove as we also use the OPTIMAL vs FEASIBLE status for that.
      bool all_solutions_were_found = 5;
      Specified by:
      getAllSolutionsWereFound in interface CpSolverResponseOrBuilder
      Returns:
      The allSolutionsWereFound.

    • setAllSolutionsWereFound

      public CpSolverResponse.Builder setAllSolutionsWereFound​(boolean value)
       This will be true iff the solver was asked to find all solutions to a
 satisfiability problem (or all optimal solutions to an optimization
 problem), and it was successful in doing so.
 TODO(user): Remove as we also use the OPTIMAL vs FEASIBLE status for that.
      bool all_solutions_were_found = 5;
      Parameters:
      value - The allSolutionsWereFound to set.
      Returns:
      This builder for chaining.

    • clearAllSolutionsWereFound

      public CpSolverResponse.Builder clearAllSolutionsWereFound()
       This will be true iff the solver was asked to find all solutions to a
 satisfiability problem (or all optimal solutions to an optimization
 problem), and it was successful in doing so.
 TODO(user): Remove as we also use the OPTIMAL vs FEASIBLE status for that.
      bool all_solutions_were_found = 5;
      Returns:
      This builder for chaining.

    • getNumBooleans

      public long getNumBooleans()
       Some statistics about the solve.
      int64 num_booleans = 10;
      Specified by:
      getNumBooleans in interface CpSolverResponseOrBuilder
      Returns:
      The numBooleans.

    • setNumBooleans

      public CpSolverResponse.Builder setNumBooleans​(long value)
       Some statistics about the solve.
      int64 num_booleans = 10;
      Parameters:
      value - The numBooleans to set.
      Returns:
      This builder for chaining.

    • clearNumBooleans

      public CpSolverResponse.Builder clearNumBooleans()
       Some statistics about the solve.
      int64 num_booleans = 10;
      Returns:
      This builder for chaining.

    • getNumConflicts

      public long getNumConflicts()
      int64 num_conflicts = 11;
      Specified by:
      getNumConflicts in interface CpSolverResponseOrBuilder
      Returns:
      The numConflicts.

    • setNumConflicts

      public CpSolverResponse.Builder setNumConflicts​(long value)
      int64 num_conflicts = 11;
      Parameters:
      value - The numConflicts to set.
      Returns:
      This builder for chaining.

    • clearNumConflicts

      public CpSolverResponse.Builder clearNumConflicts()
      int64 num_conflicts = 11;
      Returns:
      This builder for chaining.

    • getNumBranches

      public long getNumBranches()
      int64 num_branches = 12;
      Specified by:
      getNumBranches in interface CpSolverResponseOrBuilder
      Returns:
      The numBranches.

    • setNumBranches

      public CpSolverResponse.Builder setNumBranches​(long value)
      int64 num_branches = 12;
      Parameters:
      value - The numBranches to set.
      Returns:
      This builder for chaining.

    • clearNumBranches

      public CpSolverResponse.Builder clearNumBranches()
      int64 num_branches = 12;
      Returns:
      This builder for chaining.

    • getNumBinaryPropagations

      public long getNumBinaryPropagations()
      int64 num_binary_propagations = 13;
      Specified by:
      getNumBinaryPropagations in interface CpSolverResponseOrBuilder
      Returns:
      The numBinaryPropagations.

    • setNumBinaryPropagations

      public CpSolverResponse.Builder setNumBinaryPropagations​(long value)
      int64 num_binary_propagations = 13;
      Parameters:
      value - The numBinaryPropagations to set.
      Returns:
      This builder for chaining.

    • clearNumBinaryPropagations

      public CpSolverResponse.Builder clearNumBinaryPropagations()
      int64 num_binary_propagations = 13;
      Returns:
      This builder for chaining.

    • getNumIntegerPropagations

      public long getNumIntegerPropagations()
      int64 num_integer_propagations = 14;
      Specified by:
      getNumIntegerPropagations in interface CpSolverResponseOrBuilder
      Returns:
      The numIntegerPropagations.

    • setNumIntegerPropagations

      public CpSolverResponse.Builder setNumIntegerPropagations​(long value)
      int64 num_integer_propagations = 14;
      Parameters:
      value - The numIntegerPropagations to set.
      Returns:
      This builder for chaining.

    • clearNumIntegerPropagations

      public CpSolverResponse.Builder clearNumIntegerPropagations()
      int64 num_integer_propagations = 14;
      Returns:
      This builder for chaining.

    • getNumRestarts

      public long getNumRestarts()
      int64 num_restarts = 24;
      Specified by:
      getNumRestarts in interface CpSolverResponseOrBuilder
      Returns:
      The numRestarts.

    • setNumRestarts

      public CpSolverResponse.Builder setNumRestarts​(long value)
      int64 num_restarts = 24;
      Parameters:
      value - The numRestarts to set.
      Returns:
      This builder for chaining.

    • clearNumRestarts

      public CpSolverResponse.Builder clearNumRestarts()
      int64 num_restarts = 24;
      Returns:
      This builder for chaining.

    • getNumLpIterations

      public long getNumLpIterations()
      int64 num_lp_iterations = 25;
      Specified by:
      getNumLpIterations in interface CpSolverResponseOrBuilder
      Returns:
      The numLpIterations.

    • setNumLpIterations

      public CpSolverResponse.Builder setNumLpIterations​(long value)
      int64 num_lp_iterations = 25;
      Parameters:
      value - The numLpIterations to set.
      Returns:
      This builder for chaining.

    • clearNumLpIterations

      public CpSolverResponse.Builder clearNumLpIterations()
      int64 num_lp_iterations = 25;
      Returns:
      This builder for chaining.

    • getWallTime

      public double getWallTime()
      double wall_time = 15;
      Specified by:
      getWallTime in interface CpSolverResponseOrBuilder
      Returns:
      The wallTime.

    • setWallTime

      public CpSolverResponse.Builder setWallTime​(double value)
      double wall_time = 15;
      Parameters:
      value - The wallTime to set.
      Returns:
      This builder for chaining.

    • clearWallTime

      public CpSolverResponse.Builder clearWallTime()
      double wall_time = 15;
      Returns:
      This builder for chaining.

    • getUserTime

      public double getUserTime()
      double user_time = 16;
      Specified by:
      getUserTime in interface CpSolverResponseOrBuilder
      Returns:
      The userTime.

    • setUserTime

      public CpSolverResponse.Builder setUserTime​(double value)
      double user_time = 16;
      Parameters:
      value - The userTime to set.
      Returns:
      This builder for chaining.

    • clearUserTime

      public CpSolverResponse.Builder clearUserTime()
      double user_time = 16;
      Returns:
      This builder for chaining.

    • getDeterministicTime

      public double getDeterministicTime()
      double deterministic_time = 17;
      Specified by:
      getDeterministicTime in interface CpSolverResponseOrBuilder
      Returns:
      The deterministicTime.

    • setDeterministicTime

      public CpSolverResponse.Builder setDeterministicTime​(double value)
      double deterministic_time = 17;
      Parameters:
      value - The deterministicTime to set.
      Returns:
      This builder for chaining.

    • clearDeterministicTime

      public CpSolverResponse.Builder clearDeterministicTime()
      double deterministic_time = 17;
      Returns:
      This builder for chaining.

    • getPrimalIntegral

      public double getPrimalIntegral()
      double primal_integral = 22;
      Specified by:
      getPrimalIntegral in interface CpSolverResponseOrBuilder
      Returns:
      The primalIntegral.

    • setPrimalIntegral

      public CpSolverResponse.Builder setPrimalIntegral​(double value)
      double primal_integral = 22;
      Parameters:
      value - The primalIntegral to set.
      Returns:
      This builder for chaining.

    • clearPrimalIntegral

      public CpSolverResponse.Builder clearPrimalIntegral()
      double primal_integral = 22;
      Returns:
      This builder for chaining.

    • getSolutionInfo

      public java.lang.String getSolutionInfo()
       Additional information about how the solution was found.
      string solution_info = 20;
      Specified by:
      getSolutionInfo in interface CpSolverResponseOrBuilder
      Returns:
      The solutionInfo.

    • getSolutionInfoBytes

      public com.google.protobuf.ByteString getSolutionInfoBytes()
       Additional information about how the solution was found.
      string solution_info = 20;
      Specified by:
      getSolutionInfoBytes in interface CpSolverResponseOrBuilder
      Returns:
      The bytes for solutionInfo.

    • setSolutionInfo

      public CpSolverResponse.Builder setSolutionInfo​(java.lang.String value)
       Additional information about how the solution was found.
      string solution_info = 20;
      Parameters:
      value - The solutionInfo to set.
      Returns:
      This builder for chaining.

    • clearSolutionInfo

      public CpSolverResponse.Builder clearSolutionInfo()
       Additional information about how the solution was found.
      string solution_info = 20;
      Returns:
      This builder for chaining.

    • setSolutionInfoBytes

      public CpSolverResponse.Builder setSolutionInfoBytes​(com.google.protobuf.ByteString value)
       Additional information about how the solution was found.
      string solution_info = 20;
      Parameters:
      value - The bytes for solutionInfo to set.
      Returns:
      This builder for chaining.

    • getSolveLog

      public java.lang.String getSolveLog()
       The solve log will be filled if the parameter log_to_response is set to
 true.
      string solve_log = 26;
      Specified by:
      getSolveLog in interface CpSolverResponseOrBuilder
      Returns:
      The solveLog.

    • getSolveLogBytes

      public com.google.protobuf.ByteString getSolveLogBytes()
       The solve log will be filled if the parameter log_to_response is set to
 true.
      string solve_log = 26;
      Specified by:
      getSolveLogBytes in interface CpSolverResponseOrBuilder
      Returns:
      The bytes for solveLog.

    • setSolveLog

      public CpSolverResponse.Builder setSolveLog​(java.lang.String value)
       The solve log will be filled if the parameter log_to_response is set to
 true.
      string solve_log = 26;
      Parameters:
      value - The solveLog to set.
      Returns:
      This builder for chaining.

    • clearSolveLog

      public CpSolverResponse.Builder clearSolveLog()
       The solve log will be filled if the parameter log_to_response is set to
 true.
      string solve_log = 26;
      Returns:
      This builder for chaining.

    • setSolveLogBytes

      public CpSolverResponse.Builder setSolveLogBytes​(com.google.protobuf.ByteString value)
       The solve log will be filled if the parameter log_to_response is set to
 true.
      string solve_log = 26;
      Parameters:
      value - The bytes for solveLog to set.
      Returns:
      This builder for chaining.

    • setUnknownFields

      public final CpSolverResponse.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
      Specified by:
      setUnknownFields in interface com.google.protobuf.Message.Builder
      Overrides:
      setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>

    • mergeUnknownFields

      public final CpSolverResponse.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
      Specified by:
      mergeUnknownFields in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<CpSolverResponse.Builder>