public static final class CpSolverResponse.Builder extends com.google.protobuf.GeneratedMessage.Builder<CpSolverResponse.Builder> implements CpSolverResponseOrBuilder
The response returned by a solver trying to solve a CpModelProto. Next id: 31Protobuf type
operations_research.sat.CpSolverResponse| Modifier and Type | Method and Description |
|---|---|
CpSolverResponse.Builder |
addAdditionalSolutions(CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
addAdditionalSolutions(CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
addAdditionalSolutions(int index,
CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
addAdditionalSolutions(int index,
CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverSolution.Builder |
addAdditionalSolutionsBuilder()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverSolution.Builder |
addAdditionalSolutionsBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
addAllAdditionalSolutions(java.lang.Iterable<? extends CpSolverSolution> values)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
addAllSolution(java.lang.Iterable<? extends java.lang.Long> values)
A feasible solution to the given problem.
|
CpSolverResponse.Builder |
addAllSufficientAssumptionsForInfeasibility(java.lang.Iterable<? extends java.lang.Integer> values)
A subset of the model "assumptions" field.
|
CpSolverResponse.Builder |
addAllTightenedVariables(java.lang.Iterable<? extends IntegerVariableProto> values)
Advanced usage.
|
CpSolverResponse.Builder |
addSolution(long value)
A feasible solution to the given problem.
|
CpSolverResponse.Builder |
addSufficientAssumptionsForInfeasibility(int value)
A subset of the model "assumptions" field.
|
CpSolverResponse.Builder |
addTightenedVariables(IntegerVariableProto.Builder builderForValue)
Advanced usage.
|
CpSolverResponse.Builder |
addTightenedVariables(IntegerVariableProto value)
Advanced usage.
|
CpSolverResponse.Builder |
addTightenedVariables(int index,
IntegerVariableProto.Builder builderForValue)
Advanced usage.
|
CpSolverResponse.Builder |
addTightenedVariables(int index,
IntegerVariableProto value)
Advanced usage.
|
IntegerVariableProto.Builder |
addTightenedVariablesBuilder()
Advanced usage.
|
IntegerVariableProto.Builder |
addTightenedVariablesBuilder(int index)
Advanced usage.
|
CpSolverResponse |
build() |
CpSolverResponse |
buildPartial() |
CpSolverResponse.Builder |
clear() |
CpSolverResponse.Builder |
clearAdditionalSolutions()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
clearBestObjectiveBound()
Only make sense for an optimization problem.
|
CpSolverResponse.Builder |
clearDeterministicTime()
double deterministic_time = 17; |
CpSolverResponse.Builder |
clearGapIntegral()
The integral of log(1 + absolute_objective_gap) over time.
|
CpSolverResponse.Builder |
clearInnerObjectiveLowerBound()
Advanced usage.
|
CpSolverResponse.Builder |
clearIntegerObjective()
Contains the integer objective optimized internally.
|
CpSolverResponse.Builder |
clearNumBinaryPropagations()
int64 num_binary_propagations = 13; |
CpSolverResponse.Builder |
clearNumBooleans()
int64 num_booleans = 10; |
CpSolverResponse.Builder |
clearNumBranches()
int64 num_branches = 12; |
CpSolverResponse.Builder |
clearNumConflicts()
int64 num_conflicts = 11; |
CpSolverResponse.Builder |
clearNumIntegerPropagations()
int64 num_integer_propagations = 14; |
CpSolverResponse.Builder |
clearNumIntegers()
Some statistics about the solve.
|
CpSolverResponse.Builder |
clearNumLpIterations()
int64 num_lp_iterations = 25; |
CpSolverResponse.Builder |
clearNumRestarts()
int64 num_restarts = 24; |
CpSolverResponse.Builder |
clearObjectiveValue()
Only make sense for an optimization problem.
|
CpSolverResponse.Builder |
clearSolution()
A feasible solution to the given problem.
|
CpSolverResponse.Builder |
clearSolutionInfo()
Additional information about how the solution was found.
|
CpSolverResponse.Builder |
clearSolveLog()
The solve log will be filled if the parameter log_to_response is set to
true.
|
CpSolverResponse.Builder |
clearStatus()
The status of the solve.
|
CpSolverResponse.Builder |
clearSufficientAssumptionsForInfeasibility()
A subset of the model "assumptions" field.
|
CpSolverResponse.Builder |
clearTightenedVariables()
Advanced usage.
|
CpSolverResponse.Builder |
clearUserTime()
double user_time = 16; |
CpSolverResponse.Builder |
clearWallTime()
The time counted from the beginning of the Solve() call.
|
CpSolverSolution |
getAdditionalSolutions(int index)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverSolution.Builder |
getAdditionalSolutionsBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
java.util.List<CpSolverSolution.Builder> |
getAdditionalSolutionsBuilderList()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
int |
getAdditionalSolutionsCount()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
java.util.List<CpSolverSolution> |
getAdditionalSolutionsList()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverSolutionOrBuilder |
getAdditionalSolutionsOrBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
java.util.List<? extends CpSolverSolutionOrBuilder> |
getAdditionalSolutionsOrBuilderList()
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
double |
getBestObjectiveBound()
Only make sense for an optimization problem.
|
CpSolverResponse |
getDefaultInstanceForType() |
static com.google.protobuf.Descriptors.Descriptor |
getDescriptor() |
com.google.protobuf.Descriptors.Descriptor |
getDescriptorForType() |
double |
getDeterministicTime()
double deterministic_time = 17; |
double |
getGapIntegral()
The integral of log(1 + absolute_objective_gap) over time.
|
long |
getInnerObjectiveLowerBound()
Advanced usage.
|
CpObjectiveProto |
getIntegerObjective()
Contains the integer objective optimized internally.
|
CpObjectiveProto.Builder |
getIntegerObjectiveBuilder()
Contains the integer objective optimized internally.
|
CpObjectiveProtoOrBuilder |
getIntegerObjectiveOrBuilder()
Contains the integer objective optimized internally.
|
long |
getNumBinaryPropagations()
int64 num_binary_propagations = 13; |
long |
getNumBooleans()
int64 num_booleans = 10; |
long |
getNumBranches()
int64 num_branches = 12; |
long |
getNumConflicts()
int64 num_conflicts = 11; |
long |
getNumIntegerPropagations()
int64 num_integer_propagations = 14; |
long |
getNumIntegers()
Some statistics about the solve.
|
long |
getNumLpIterations()
int64 num_lp_iterations = 25; |
long |
getNumRestarts()
int64 num_restarts = 24; |
double |
getObjectiveValue()
Only make sense for an optimization problem.
|
long |
getSolution(int index)
A feasible solution to the given problem.
|
int |
getSolutionCount()
A feasible solution to the given problem.
|
java.lang.String |
getSolutionInfo()
Additional information about how the solution was found.
|
com.google.protobuf.ByteString |
getSolutionInfoBytes()
Additional information about how the solution was found.
|
java.util.List<java.lang.Long> |
getSolutionList()
A feasible solution to the given problem.
|
java.lang.String |
getSolveLog()
The solve log will be filled if the parameter log_to_response is set to
true.
|
com.google.protobuf.ByteString |
getSolveLogBytes()
The solve log will be filled if the parameter log_to_response is set to
true.
|
CpSolverStatus |
getStatus()
The status of the solve.
|
int |
getStatusValue()
The status of the solve.
|
int |
getSufficientAssumptionsForInfeasibility(int index)
A subset of the model "assumptions" field.
|
int |
getSufficientAssumptionsForInfeasibilityCount()
A subset of the model "assumptions" field.
|
java.util.List<java.lang.Integer> |
getSufficientAssumptionsForInfeasibilityList()
A subset of the model "assumptions" field.
|
IntegerVariableProto |
getTightenedVariables(int index)
Advanced usage.
|
IntegerVariableProto.Builder |
getTightenedVariablesBuilder(int index)
Advanced usage.
|
java.util.List<IntegerVariableProto.Builder> |
getTightenedVariablesBuilderList()
Advanced usage.
|
int |
getTightenedVariablesCount()
Advanced usage.
|
java.util.List<IntegerVariableProto> |
getTightenedVariablesList()
Advanced usage.
|
IntegerVariableProtoOrBuilder |
getTightenedVariablesOrBuilder(int index)
Advanced usage.
|
java.util.List<? extends IntegerVariableProtoOrBuilder> |
getTightenedVariablesOrBuilderList()
Advanced usage.
|
double |
getUserTime()
double user_time = 16; |
double |
getWallTime()
The time counted from the beginning of the Solve() call.
|
boolean |
hasIntegerObjective()
Contains the integer objective optimized internally.
|
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable |
internalGetFieldAccessorTable() |
boolean |
isInitialized() |
CpSolverResponse.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
CpSolverResponse.Builder |
mergeFrom(CpSolverResponse other) |
CpSolverResponse.Builder |
mergeFrom(com.google.protobuf.Message other) |
CpSolverResponse.Builder |
mergeIntegerObjective(CpObjectiveProto value)
Contains the integer objective optimized internally.
|
CpSolverResponse.Builder |
removeAdditionalSolutions(int index)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
removeTightenedVariables(int index)
Advanced usage.
|
CpSolverResponse.Builder |
setAdditionalSolutions(int index,
CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
setAdditionalSolutions(int index,
CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we
copy all the solutions from our internal solution pool here.
|
CpSolverResponse.Builder |
setBestObjectiveBound(double value)
Only make sense for an optimization problem.
|
CpSolverResponse.Builder |
setDeterministicTime(double value)
double deterministic_time = 17; |
CpSolverResponse.Builder |
setGapIntegral(double value)
The integral of log(1 + absolute_objective_gap) over time.
|
CpSolverResponse.Builder |
setInnerObjectiveLowerBound(long value)
Advanced usage.
|
CpSolverResponse.Builder |
setIntegerObjective(CpObjectiveProto.Builder builderForValue)
Contains the integer objective optimized internally.
|
CpSolverResponse.Builder |
setIntegerObjective(CpObjectiveProto value)
Contains the integer objective optimized internally.
|
CpSolverResponse.Builder |
setNumBinaryPropagations(long value)
int64 num_binary_propagations = 13; |
CpSolverResponse.Builder |
setNumBooleans(long value)
int64 num_booleans = 10; |
CpSolverResponse.Builder |
setNumBranches(long value)
int64 num_branches = 12; |
CpSolverResponse.Builder |
setNumConflicts(long value)
int64 num_conflicts = 11; |
CpSolverResponse.Builder |
setNumIntegerPropagations(long value)
int64 num_integer_propagations = 14; |
CpSolverResponse.Builder |
setNumIntegers(long value)
Some statistics about the solve.
|
CpSolverResponse.Builder |
setNumLpIterations(long value)
int64 num_lp_iterations = 25; |
CpSolverResponse.Builder |
setNumRestarts(long value)
int64 num_restarts = 24; |
CpSolverResponse.Builder |
setObjectiveValue(double value)
Only make sense for an optimization problem.
|
CpSolverResponse.Builder |
setSolution(int index,
long value)
A feasible solution to the given problem.
|
CpSolverResponse.Builder |
setSolutionInfo(java.lang.String value)
Additional information about how the solution was found.
|
CpSolverResponse.Builder |
setSolutionInfoBytes(com.google.protobuf.ByteString value)
Additional information about how the solution was found.
|
CpSolverResponse.Builder |
setSolveLog(java.lang.String value)
The solve log will be filled if the parameter log_to_response is set to
true.
|
CpSolverResponse.Builder |
setSolveLogBytes(com.google.protobuf.ByteString value)
The solve log will be filled if the parameter log_to_response is set to
true.
|
CpSolverResponse.Builder |
setStatus(CpSolverStatus value)
The status of the solve.
|
CpSolverResponse.Builder |
setStatusValue(int value)
The status of the solve.
|
CpSolverResponse.Builder |
setSufficientAssumptionsForInfeasibility(int index,
int value)
A subset of the model "assumptions" field.
|
CpSolverResponse.Builder |
setTightenedVariables(int index,
IntegerVariableProto.Builder builderForValue)
Advanced usage.
|
CpSolverResponse.Builder |
setTightenedVariables(int index,
IntegerVariableProto value)
Advanced usage.
|
CpSolverResponse.Builder |
setUserTime(double value)
double user_time = 16; |
CpSolverResponse.Builder |
setWallTime(double value)
The time counted from the beginning of the Solve() call.
|
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<CpSolverResponse.Builder>public CpSolverResponse.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessage.Builder<CpSolverResponse.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<CpSolverResponse.Builder>public CpSolverResponse getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic CpSolverResponse build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic CpSolverResponse buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic CpSolverResponse.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<CpSolverResponse.Builder>public CpSolverResponse.Builder mergeFrom(CpSolverResponse other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessage.Builder<CpSolverResponse.Builder>public CpSolverResponse.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<CpSolverResponse.Builder>java.io.IOExceptionpublic int getStatusValue()
The status of the solve.
.operations_research.sat.CpSolverStatus status = 1;getStatusValue in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setStatusValue(int value)
The status of the solve.
.operations_research.sat.CpSolverStatus status = 1;value - The enum numeric value on the wire for status to set.public CpSolverStatus getStatus()
The status of the solve.
.operations_research.sat.CpSolverStatus status = 1;getStatus in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setStatus(CpSolverStatus value)
The status of the solve.
.operations_research.sat.CpSolverStatus status = 1;value - The status to set.public CpSolverResponse.Builder clearStatus()
The status of the solve.
.operations_research.sat.CpSolverStatus status = 1;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;getSolutionList in interface CpSolverResponseOrBuilderpublic 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;getSolutionCount in interface CpSolverResponseOrBuilderpublic 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;getSolution in interface CpSolverResponseOrBuilderindex - The index of the element to return.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;index - The index to set the value at.value - The solution to set.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;value - The solution to add.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;values - The solution to add.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;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;getObjectiveValue in interface CpSolverResponseOrBuilderpublic 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;value - The objectiveValue to set.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;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;getBestObjectiveBound in interface CpSolverResponseOrBuilderpublic 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;value - The bestObjectiveBound to set.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;public java.util.List<CpSolverSolution> getAdditionalSolutionsList()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;getAdditionalSolutionsList in interface CpSolverResponseOrBuilderpublic int getAdditionalSolutionsCount()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;getAdditionalSolutionsCount in interface CpSolverResponseOrBuilderpublic CpSolverSolution getAdditionalSolutions(int index)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;getAdditionalSolutions in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setAdditionalSolutions(int index, CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder setAdditionalSolutions(int index, CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder addAdditionalSolutions(CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder addAdditionalSolutions(int index, CpSolverSolution value)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder addAdditionalSolutions(CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder addAdditionalSolutions(int index, CpSolverSolution.Builder builderForValue)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder addAllAdditionalSolutions(java.lang.Iterable<? extends CpSolverSolution> values)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder clearAdditionalSolutions()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverResponse.Builder removeAdditionalSolutions(int index)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverSolution.Builder getAdditionalSolutionsBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverSolutionOrBuilder getAdditionalSolutionsOrBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;getAdditionalSolutionsOrBuilder in interface CpSolverResponseOrBuilderpublic java.util.List<? extends CpSolverSolutionOrBuilder> getAdditionalSolutionsOrBuilderList()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;getAdditionalSolutionsOrBuilderList in interface CpSolverResponseOrBuilderpublic CpSolverSolution.Builder addAdditionalSolutionsBuilder()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public CpSolverSolution.Builder addAdditionalSolutionsBuilder(int index)
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;public java.util.List<CpSolverSolution.Builder> getAdditionalSolutionsBuilderList()
If the parameter fill_additional_solutions_in_response is set, then we copy all the solutions from our internal solution pool here. Note that the one returned in the solution field will likely appear here too. Do not rely on the solutions order as it depends on our internal representation (after postsolve).
repeated .operations_research.sat.CpSolverSolution additional_solutions = 27;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;getTightenedVariablesList in interface CpSolverResponseOrBuilderpublic 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;getTightenedVariablesCount in interface CpSolverResponseOrBuilderpublic 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;getTightenedVariables in interface CpSolverResponseOrBuilderpublic 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;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;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;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;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;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;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;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;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;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;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;getTightenedVariablesOrBuilder in interface CpSolverResponseOrBuilderpublic 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;getTightenedVariablesOrBuilderList in interface CpSolverResponseOrBuilderpublic 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;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;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;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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;getSufficientAssumptionsForInfeasibilityList in interface CpSolverResponseOrBuilderpublic 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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;getSufficientAssumptionsForInfeasibilityCount in interface CpSolverResponseOrBuilderpublic 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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;getSufficientAssumptionsForInfeasibility in interface CpSolverResponseOrBuilderindex - The index of the element to return.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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;index - The index to set the value at.value - The sufficientAssumptionsForInfeasibility to set.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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;value - The sufficientAssumptionsForInfeasibility to add.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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;values - The sufficientAssumptionsForInfeasibility to add.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. Important: Currently, this is minimized only in single-thread and if the problem is not an optimization problem, otherwise, it will always include all the assumptions. TODO(user): Allows for returning multiple core at once.
repeated int32 sufficient_assumptions_for_infeasibility = 23;public boolean hasIntegerObjective()
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;hasIntegerObjective in interface CpSolverResponseOrBuilderpublic CpObjectiveProto getIntegerObjective()
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;getIntegerObjective in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setIntegerObjective(CpObjectiveProto value)
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;public CpSolverResponse.Builder setIntegerObjective(CpObjectiveProto.Builder builderForValue)
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;public CpSolverResponse.Builder mergeIntegerObjective(CpObjectiveProto value)
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;public CpSolverResponse.Builder clearIntegerObjective()
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;public CpObjectiveProto.Builder getIntegerObjectiveBuilder()
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;public CpObjectiveProtoOrBuilder getIntegerObjectiveOrBuilder()
Contains the integer objective optimized internally. This is only filled if the problem had a floating point objective, and on the final response, not the ones given to callbacks.
.operations_research.sat.CpObjectiveProto integer_objective = 28;getIntegerObjectiveOrBuilder in interface CpSolverResponseOrBuilderpublic long getInnerObjectiveLowerBound()
Advanced usage. A lower bound on the inner integer expression of the objective. This is either a bound on the expression in the returned integer_objective or on the integer expression of the original objective if the problem already has an integer objective.
int64 inner_objective_lower_bound = 29;getInnerObjectiveLowerBound in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setInnerObjectiveLowerBound(long value)
Advanced usage. A lower bound on the inner integer expression of the objective. This is either a bound on the expression in the returned integer_objective or on the integer expression of the original objective if the problem already has an integer objective.
int64 inner_objective_lower_bound = 29;value - The innerObjectiveLowerBound to set.public CpSolverResponse.Builder clearInnerObjectiveLowerBound()
Advanced usage. A lower bound on the inner integer expression of the objective. This is either a bound on the expression in the returned integer_objective or on the integer expression of the original objective if the problem already has an integer objective.
int64 inner_objective_lower_bound = 29;public long getNumIntegers()
Some statistics about the solve. Important: in multithread, this correspond the statistics of the first subsolver. Which is usually the one with the user defined parameters. Or the default-search if none are specified.
int64 num_integers = 30;getNumIntegers in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumIntegers(long value)
Some statistics about the solve. Important: in multithread, this correspond the statistics of the first subsolver. Which is usually the one with the user defined parameters. Or the default-search if none are specified.
int64 num_integers = 30;value - The numIntegers to set.public CpSolverResponse.Builder clearNumIntegers()
Some statistics about the solve. Important: in multithread, this correspond the statistics of the first subsolver. Which is usually the one with the user defined parameters. Or the default-search if none are specified.
int64 num_integers = 30;public long getNumBooleans()
int64 num_booleans = 10;getNumBooleans in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumBooleans(long value)
int64 num_booleans = 10;value - The numBooleans to set.public CpSolverResponse.Builder clearNumBooleans()
int64 num_booleans = 10;public long getNumConflicts()
int64 num_conflicts = 11;getNumConflicts in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumConflicts(long value)
int64 num_conflicts = 11;value - The numConflicts to set.public CpSolverResponse.Builder clearNumConflicts()
int64 num_conflicts = 11;public long getNumBranches()
int64 num_branches = 12;getNumBranches in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumBranches(long value)
int64 num_branches = 12;value - The numBranches to set.public CpSolverResponse.Builder clearNumBranches()
int64 num_branches = 12;public long getNumBinaryPropagations()
int64 num_binary_propagations = 13;getNumBinaryPropagations in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumBinaryPropagations(long value)
int64 num_binary_propagations = 13;value - The numBinaryPropagations to set.public CpSolverResponse.Builder clearNumBinaryPropagations()
int64 num_binary_propagations = 13;public long getNumIntegerPropagations()
int64 num_integer_propagations = 14;getNumIntegerPropagations in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumIntegerPropagations(long value)
int64 num_integer_propagations = 14;value - The numIntegerPropagations to set.public CpSolverResponse.Builder clearNumIntegerPropagations()
int64 num_integer_propagations = 14;public long getNumRestarts()
int64 num_restarts = 24;getNumRestarts in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumRestarts(long value)
int64 num_restarts = 24;value - The numRestarts to set.public CpSolverResponse.Builder clearNumRestarts()
int64 num_restarts = 24;public long getNumLpIterations()
int64 num_lp_iterations = 25;getNumLpIterations in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setNumLpIterations(long value)
int64 num_lp_iterations = 25;value - The numLpIterations to set.public CpSolverResponse.Builder clearNumLpIterations()
int64 num_lp_iterations = 25;public double getWallTime()
The time counted from the beginning of the Solve() call.
double wall_time = 15;getWallTime in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setWallTime(double value)
The time counted from the beginning of the Solve() call.
double wall_time = 15;value - The wallTime to set.public CpSolverResponse.Builder clearWallTime()
The time counted from the beginning of the Solve() call.
double wall_time = 15;public double getUserTime()
double user_time = 16;getUserTime in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setUserTime(double value)
double user_time = 16;value - The userTime to set.public CpSolverResponse.Builder clearUserTime()
double user_time = 16;public double getDeterministicTime()
double deterministic_time = 17;getDeterministicTime in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setDeterministicTime(double value)
double deterministic_time = 17;value - The deterministicTime to set.public CpSolverResponse.Builder clearDeterministicTime()
double deterministic_time = 17;public double getGapIntegral()
The integral of log(1 + absolute_objective_gap) over time.
double gap_integral = 22;getGapIntegral in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setGapIntegral(double value)
The integral of log(1 + absolute_objective_gap) over time.
double gap_integral = 22;value - The gapIntegral to set.public CpSolverResponse.Builder clearGapIntegral()
The integral of log(1 + absolute_objective_gap) over time.
double gap_integral = 22;public java.lang.String getSolutionInfo()
Additional information about how the solution was found. It also stores model or parameters errors that caused the model to be invalid.
string solution_info = 20;getSolutionInfo in interface CpSolverResponseOrBuilderpublic com.google.protobuf.ByteString getSolutionInfoBytes()
Additional information about how the solution was found. It also stores model or parameters errors that caused the model to be invalid.
string solution_info = 20;getSolutionInfoBytes in interface CpSolverResponseOrBuilderpublic CpSolverResponse.Builder setSolutionInfo(java.lang.String value)
Additional information about how the solution was found. It also stores model or parameters errors that caused the model to be invalid.
string solution_info = 20;value - The solutionInfo to set.public CpSolverResponse.Builder clearSolutionInfo()
Additional information about how the solution was found. It also stores model or parameters errors that caused the model to be invalid.
string solution_info = 20;public CpSolverResponse.Builder setSolutionInfoBytes(com.google.protobuf.ByteString value)
Additional information about how the solution was found. It also stores model or parameters errors that caused the model to be invalid.
string solution_info = 20;value - The bytes for solutionInfo to set.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;getSolveLog in interface CpSolverResponseOrBuilderpublic 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;getSolveLogBytes in interface CpSolverResponseOrBuilderpublic 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;value - The solveLog to set.public CpSolverResponse.Builder clearSolveLog()
The solve log will be filled if the parameter log_to_response is set to true.
string solve_log = 26;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;value - The bytes for solveLog to set.Copyright © 2024. All rights reserved.