Uses of Class
com.google.ortools.bop.BopParameters.Builder
Packages that use BopParameters.Builder
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Uses of BopParameters.Builder in com.google.ortools.bop
Methods in com.google.ortools.bop that return BopParameters.BuilderModifier and TypeMethodDescriptionBopParameters.Builder.addAllSolverOptimizerSets(Iterable<? extends BopSolverOptimizerSet> values) List of set of optimizers to be run by the solvers.BopParameters.Builder.addSolverOptimizerSets(int index, BopSolverOptimizerSet value) List of set of optimizers to be run by the solvers.BopParameters.Builder.addSolverOptimizerSets(int index, BopSolverOptimizerSet.Builder builderForValue) List of set of optimizers to be run by the solvers.BopParameters.Builder.addSolverOptimizerSets(BopSolverOptimizerSet value) List of set of optimizers to be run by the solvers.BopParameters.Builder.addSolverOptimizerSets(BopSolverOptimizerSet.Builder builderForValue) List of set of optimizers to be run by the solvers.BopParameters.Builder.clear()BopParameters.Builder.clearComputeEstimatedImpact()Compute estimated impact at each iteration when true; only once when false.BopParameters.Builder.clearDecomposedProblemMinTimeInSeconds()HACK.BopParameters.Builder.clearDecomposerNumVariablesThreshold()Only try to decompose the problem when the number of variables is greater than the threshold.BopParameters.Builder.clearDefaultSolverOptimizerSets()optional string default_solver_optimizer_sets = 33 [default = "methods:{type:LOCAL_SEARCH } methods:{type:RANDOM_FIRST_SOLUTION } methods:{type:LINEAR_RELAXATION } methods:{type:LP_FIRST_SOLUTION } methods:{type:OBJECTIVE_FIRST_SOLUTION } methods:{type:USER_GUIDED_FIRST_SOLUTION } methods:{type:RANDOM_CONSTRAINT_LNS_GUIDED_BY_LP } methods:{type:RANDOM_VARIABLE_LNS_GUIDED_BY_LP } methods:{type:RELATION_GRAPH_LNS } methods:{type:RELATION_GRAPH_LNS_GUIDED_BY_LP } methods:{type:RANDOM_CONSTRAINT_LNS } methods:{type:RANDOM_VARIABLE_LNS } methods:{type:SAT_CORE_BASED } methods:{type:COMPLETE_LNS } "];BopParameters.Builder.clearExploitSymmetryInSatFirstSolution()If true, find and exploit symmetries in proving satisfiability in the first problem.BopParameters.Builder.clearGuidedSatConflictsChunk()The first solutions based on guided SAT will work in chunk of that many conflicts at the time.BopParameters.Builder.clearLogSearchProgress()Whether the solver should log the search progress to LOG(INFO).BopParameters.Builder.clearLpMaxDeterministicTime()The max deterministic time given to the LP solver each time it is called.BopParameters.Builder.clearMaxDeterministicTime()Maximum time allowed in deterministic time to solve a problem.BopParameters.Builder.clearMaxLpSolveForFeasibilityProblems()The maximum number of time the LP solver will run to feasibility for pure feasibility problems (with a constant-valued objective function).BopParameters.Builder.clearMaxNumberOfBacktracksInLs()Maximum number of backtracks times the number of variables in Local Search, ie. max num backtracks == max_number_of_backtracks_in_ls / num variables.BopParameters.Builder.clearMaxNumberOfConflictsForQuickCheck()The number of conflicts the SAT solver has to solve a random LNS subproblem for the quick check of infeasibility.BopParameters.Builder.clearMaxNumberOfConflictsInRandomLns()The number of conflicts the SAT solver has to solve a random LNS subproblem.BopParameters.Builder.clearMaxNumberOfConflictsInRandomSolutionGeneration()The number of conflicts the SAT solver has to generate a random solution.BopParameters.Builder.clearMaxNumberOfConsecutiveFailingOptimizerCalls()Maximum number of consecutive optimizer calls without improving the current solution.BopParameters.Builder.clearMaxNumberOfExploredAssignmentsPerTryInLs()The maximum number of assignments the Local Search iterates on during one try.BopParameters.Builder.clearMaxNumBrokenConstraintsInLs()Abort the LS search tree as soon as strictly more than this number of constraints are broken.BopParameters.Builder.clearMaxNumDecisionsInLs()Maximum number of cascading decisions the solver might use to repair the current solution in the LS.BopParameters.Builder.clearMaxTimeInSeconds()Maximum time allowed in seconds to solve a problem.BopParameters.Builder.clearNumberOfSolvers()The number of solvers used to run Bop.BopParameters.Builder.clearNumBopSolversUsedByDecomposition()The number of BopSolver created (thread pool workers) used by the integral solver to solve a decomposed problem.BopParameters.Builder.clearNumRandomLnsTries()Number of tries in the random lns.BopParameters.Builder.clearNumRelaxedVars()Number of variables to relax in the exhaustive Large Neighborhood Search.BopParameters.Builder.clearPruneSearchTree()Avoid exploring both branches (b, a, ...) and (a, b, ...).BopParameters.Builder.clearRandomSeed()The seed used to initialize the random generator.BopParameters.Builder.clearRelativeGapLimit()Limit used to stop the optimization as soon as the relative gap is smaller than the given value.BopParameters.Builder.clearSolverOptimizerSets()List of set of optimizers to be run by the solvers.BopParameters.Builder.clearSortConstraintsByNumTerms()Sort constraints by increasing total number of terms instead of number of contributing terms.BopParameters.Builder.clearSynchronizationType()optional .operations_research.bop.BopParameters.ThreadSynchronizationType synchronization_type = 25 [default = NO_SYNCHRONIZATION];BopParameters.Builder.clearUseLearnedBinaryClausesInLp()Whether we use the learned binary clauses in the Linear Relaxation.BopParameters.Builder.clearUseLpLns()Use Large Neighborhood Search based on the LP relaxation.BopParameters.Builder.clearUseLpStrongBranching()Use strong branching in the linear relaxation optimizer.BopParameters.Builder.clearUsePotentialOneFlipRepairsInLs()Whether we keep a list of variable that can potentially repair in one flip all the current infeasible constraints (such variable must at least appear in all the infeasible constraints for this to happen).BopParameters.Builder.clearUseRandomLns()Use the random Large Neighborhood Search instead of the exhaustive one.BopParameters.Builder.clearUseSatToChooseLnsNeighbourhood()Whether we use sat propagation to choose the lns neighbourhood.BopParameters.Builder.clearUseSymmetry()If true, find and exploit the eventual symmetries of the problem.BopParameters.Builder.clearUseTranspositionTableInLs()Whether we use an hash set during the LS to avoid exploring more than once the "same" state.BopParameters.Builder.mergeFrom(BopParameters other) BopParameters.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) BopParameters.Builder.mergeFrom(com.google.protobuf.Message other) static BopParameters.BuilderBopParameters.newBuilder()static BopParameters.BuilderBopParameters.newBuilder(BopParameters prototype) BopParameters.newBuilderForType()protected BopParameters.BuilderBopParameters.newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent) BopParameters.Builder.removeSolverOptimizerSets(int index) List of set of optimizers to be run by the solvers.BopParameters.Builder.setComputeEstimatedImpact(boolean value) Compute estimated impact at each iteration when true; only once when false.BopParameters.Builder.setDecomposedProblemMinTimeInSeconds(double value) HACK.BopParameters.Builder.setDecomposerNumVariablesThreshold(int value) Only try to decompose the problem when the number of variables is greater than the threshold.BopParameters.Builder.setDefaultSolverOptimizerSets(String value) optional string default_solver_optimizer_sets = 33 [default = "methods:{type:LOCAL_SEARCH } methods:{type:RANDOM_FIRST_SOLUTION } methods:{type:LINEAR_RELAXATION } methods:{type:LP_FIRST_SOLUTION } methods:{type:OBJECTIVE_FIRST_SOLUTION } methods:{type:USER_GUIDED_FIRST_SOLUTION } methods:{type:RANDOM_CONSTRAINT_LNS_GUIDED_BY_LP } methods:{type:RANDOM_VARIABLE_LNS_GUIDED_BY_LP } methods:{type:RELATION_GRAPH_LNS } methods:{type:RELATION_GRAPH_LNS_GUIDED_BY_LP } methods:{type:RANDOM_CONSTRAINT_LNS } methods:{type:RANDOM_VARIABLE_LNS } methods:{type:SAT_CORE_BASED } methods:{type:COMPLETE_LNS } "];BopParameters.Builder.setDefaultSolverOptimizerSetsBytes(com.google.protobuf.ByteString value) optional string default_solver_optimizer_sets = 33 [default = "methods:{type:LOCAL_SEARCH } methods:{type:RANDOM_FIRST_SOLUTION } methods:{type:LINEAR_RELAXATION } methods:{type:LP_FIRST_SOLUTION } methods:{type:OBJECTIVE_FIRST_SOLUTION } methods:{type:USER_GUIDED_FIRST_SOLUTION } methods:{type:RANDOM_CONSTRAINT_LNS_GUIDED_BY_LP } methods:{type:RANDOM_VARIABLE_LNS_GUIDED_BY_LP } methods:{type:RELATION_GRAPH_LNS } methods:{type:RELATION_GRAPH_LNS_GUIDED_BY_LP } methods:{type:RANDOM_CONSTRAINT_LNS } methods:{type:RANDOM_VARIABLE_LNS } methods:{type:SAT_CORE_BASED } methods:{type:COMPLETE_LNS } "];BopParameters.Builder.setExploitSymmetryInSatFirstSolution(boolean value) If true, find and exploit symmetries in proving satisfiability in the first problem.BopParameters.Builder.setGuidedSatConflictsChunk(int value) The first solutions based on guided SAT will work in chunk of that many conflicts at the time.BopParameters.Builder.setLogSearchProgress(boolean value) Whether the solver should log the search progress to LOG(INFO).BopParameters.Builder.setLpMaxDeterministicTime(double value) The max deterministic time given to the LP solver each time it is called.BopParameters.Builder.setMaxDeterministicTime(double value) Maximum time allowed in deterministic time to solve a problem.BopParameters.Builder.setMaxLpSolveForFeasibilityProblems(int value) The maximum number of time the LP solver will run to feasibility for pure feasibility problems (with a constant-valued objective function).BopParameters.Builder.setMaxNumberOfBacktracksInLs(long value) Maximum number of backtracks times the number of variables in Local Search, ie. max num backtracks == max_number_of_backtracks_in_ls / num variables.BopParameters.Builder.setMaxNumberOfConflictsForQuickCheck(int value) The number of conflicts the SAT solver has to solve a random LNS subproblem for the quick check of infeasibility.BopParameters.Builder.setMaxNumberOfConflictsInRandomLns(int value) The number of conflicts the SAT solver has to solve a random LNS subproblem.BopParameters.Builder.setMaxNumberOfConflictsInRandomSolutionGeneration(int value) The number of conflicts the SAT solver has to generate a random solution.BopParameters.Builder.setMaxNumberOfConsecutiveFailingOptimizerCalls(int value) Maximum number of consecutive optimizer calls without improving the current solution.BopParameters.Builder.setMaxNumberOfExploredAssignmentsPerTryInLs(long value) The maximum number of assignments the Local Search iterates on during one try.BopParameters.Builder.setMaxNumBrokenConstraintsInLs(int value) Abort the LS search tree as soon as strictly more than this number of constraints are broken.BopParameters.Builder.setMaxNumDecisionsInLs(int value) Maximum number of cascading decisions the solver might use to repair the current solution in the LS.BopParameters.Builder.setMaxTimeInSeconds(double value) Maximum time allowed in seconds to solve a problem.BopParameters.Builder.setNumberOfSolvers(int value) The number of solvers used to run Bop.BopParameters.Builder.setNumBopSolversUsedByDecomposition(int value) The number of BopSolver created (thread pool workers) used by the integral solver to solve a decomposed problem.BopParameters.Builder.setNumRandomLnsTries(int value) Number of tries in the random lns.BopParameters.Builder.setNumRelaxedVars(int value) Number of variables to relax in the exhaustive Large Neighborhood Search.BopParameters.Builder.setPruneSearchTree(boolean value) Avoid exploring both branches (b, a, ...) and (a, b, ...).BopParameters.Builder.setRandomSeed(int value) The seed used to initialize the random generator.BopParameters.Builder.setRelativeGapLimit(double value) Limit used to stop the optimization as soon as the relative gap is smaller than the given value.BopParameters.Builder.setSolverOptimizerSets(int index, BopSolverOptimizerSet value) List of set of optimizers to be run by the solvers.BopParameters.Builder.setSolverOptimizerSets(int index, BopSolverOptimizerSet.Builder builderForValue) List of set of optimizers to be run by the solvers.BopParameters.Builder.setSortConstraintsByNumTerms(boolean value) Sort constraints by increasing total number of terms instead of number of contributing terms.BopParameters.Builder.setSynchronizationType(BopParameters.ThreadSynchronizationType value) optional .operations_research.bop.BopParameters.ThreadSynchronizationType synchronization_type = 25 [default = NO_SYNCHRONIZATION];BopParameters.Builder.setUseLearnedBinaryClausesInLp(boolean value) Whether we use the learned binary clauses in the Linear Relaxation.BopParameters.Builder.setUseLpLns(boolean value) Use Large Neighborhood Search based on the LP relaxation.BopParameters.Builder.setUseLpStrongBranching(boolean value) Use strong branching in the linear relaxation optimizer.BopParameters.Builder.setUsePotentialOneFlipRepairsInLs(boolean value) Whether we keep a list of variable that can potentially repair in one flip all the current infeasible constraints (such variable must at least appear in all the infeasible constraints for this to happen).BopParameters.Builder.setUseRandomLns(boolean value) Use the random Large Neighborhood Search instead of the exhaustive one.BopParameters.Builder.setUseSatToChooseLnsNeighbourhood(boolean value) Whether we use sat propagation to choose the lns neighbourhood.BopParameters.Builder.setUseSymmetry(boolean value) If true, find and exploit the eventual symmetries of the problem.BopParameters.Builder.setUseTranspositionTableInLs(boolean value) Whether we use an hash set during the LS to avoid exploring more than once the "same" state.BopParameters.toBuilder()