Java Reference
Java Reference
Detailed Description
A constraint programming problem.
Protobuf type
Definition at line 861 of file CpModelProto.java.
Static Public Member Functions | |
| static final com.google.protobuf.Descriptors.Descriptor | getDescriptor () |
Protected Member Functions | |
| .lang.Override com.google.protobuf.GeneratedMessageV3.FieldAccessorTable | internalGetFieldAccessorTable () |
Member Function Documentation
◆ addAllAssumptions()
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inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Parameters
-
values The assumptions to add.
- Returns
- This builder for chaining.
Definition at line 2809 of file CpModelProto.java.
◆ addAllConstraints()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1724 of file CpModelProto.java.
◆ addAllSearchStrategy()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2239 of file CpModelProto.java.
◆ addAllVariables()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1452 of file CpModelProto.java.
◆ addAssumptions()
|
inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Parameters
-
value The assumptions to add.
- Returns
- This builder for chaining.
Definition at line 2784 of file CpModelProto.java.
◆ addConstraints() [1/4]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1663 of file CpModelProto.java.
◆ addConstraints() [2/4]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1696 of file CpModelProto.java.
◆ addConstraints() [3/4]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1679 of file CpModelProto.java.
◆ addConstraints() [4/4]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1710 of file CpModelProto.java.
◆ addConstraintsBuilder() [1/2]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1793 of file CpModelProto.java.
◆ addConstraintsBuilder() [2/2]
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1800 of file CpModelProto.java.
◆ addRepeatedField()
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inline |
Definition at line 1034 of file CpModelProto.java.
◆ addSearchStrategy() [1/4]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2130 of file CpModelProto.java.
◆ addSearchStrategy() [2/4]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2187 of file CpModelProto.java.
◆ addSearchStrategy() [3/4]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2158 of file CpModelProto.java.
◆ addSearchStrategy() [4/4]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2213 of file CpModelProto.java.
◆ addSearchStrategyBuilder() [1/2]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2380 of file CpModelProto.java.
◆ addSearchStrategyBuilder() [2/2]
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2399 of file CpModelProto.java.
◆ addVariables() [1/4]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1375 of file CpModelProto.java.
◆ addVariables() [2/4]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1416 of file CpModelProto.java.
◆ addVariables() [3/4]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1395 of file CpModelProto.java.
◆ addVariables() [4/4]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1434 of file CpModelProto.java.
◆ addVariablesBuilder() [1/2]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1545 of file CpModelProto.java.
◆ addVariablesBuilder() [2/2]
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1556 of file CpModelProto.java.
◆ build()
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inline |
Definition at line 948 of file CpModelProto.java.
◆ buildPartial()
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inline |
Definition at line 957 of file CpModelProto.java.
◆ clear()
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inline |
Definition at line 897 of file CpModelProto.java.
◆ clearAssumptions()
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inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Returns
- This builder for chaining.
Definition at line 2835 of file CpModelProto.java.
◆ clearConstraints()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1739 of file CpModelProto.java.
◆ clearField()
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inline |
Definition at line 1018 of file CpModelProto.java.
◆ clearName()
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inline |
For debug/logging only. Can be empty.
string name = 1;
- Returns
- This builder for chaining.
Definition at line 1248 of file CpModelProto.java.
◆ clearObjective()
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inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 1923 of file CpModelProto.java.
◆ clearOneof()
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inline |
Definition at line 1023 of file CpModelProto.java.
◆ clearSearchStrategy()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2266 of file CpModelProto.java.
◆ clearSolutionHint()
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inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Definition at line 2582 of file CpModelProto.java.
◆ clearVariables()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1471 of file CpModelProto.java.
◆ clone()
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inline |
Definition at line 1008 of file CpModelProto.java.
◆ getAssumptions()
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inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Parameters
-
index The index of the element to return.
- Returns
- The assumptions at the given index.
Implements CpModelProtoOrBuilder.
Definition at line 2735 of file CpModelProto.java.
◆ getAssumptionsCount()
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inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Returns
- The count of assumptions.
Implements CpModelProtoOrBuilder.
Definition at line 2713 of file CpModelProto.java.
◆ getAssumptionsList()
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inline |
A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Returns
- A list containing the assumptions.
Implements CpModelProtoOrBuilder.
Definition at line 2691 of file CpModelProto.java.
◆ getConstraints()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements CpModelProtoOrBuilder.
Definition at line 1622 of file CpModelProto.java.
◆ getConstraintsBuilder()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1765 of file CpModelProto.java.
◆ getConstraintsBuilderList()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1809 of file CpModelProto.java.
◆ getConstraintsCount()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements CpModelProtoOrBuilder.
Definition at line 1612 of file CpModelProto.java.
◆ getConstraintsList()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements CpModelProtoOrBuilder.
Definition at line 1602 of file CpModelProto.java.
◆ getConstraintsOrBuilder()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements CpModelProtoOrBuilder.
Definition at line 1772 of file CpModelProto.java.
◆ getConstraintsOrBuilderList()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements CpModelProtoOrBuilder.
Definition at line 1783 of file CpModelProto.java.
◆ getDefaultInstanceForType()
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inline |
Definition at line 943 of file CpModelProto.java.
◆ getDescriptor()
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inlinestatic |
Definition at line 866 of file CpModelProto.java.
◆ getDescriptorForType()
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inline |
Definition at line 938 of file CpModelProto.java.
◆ getName()
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inline |
For debug/logging only. Can be empty.
string name = 1;
- Returns
- The name.
Implements CpModelProtoOrBuilder.
Definition at line 1188 of file CpModelProto.java.
◆ getNameBytes()
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inline |
For debug/logging only. Can be empty.
string name = 1;
- Returns
- The bytes for name.
Implements CpModelProtoOrBuilder.
Definition at line 1209 of file CpModelProto.java.
◆ getObjective()
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inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
- Returns
- The objective.
Implements CpModelProtoOrBuilder.
Definition at line 1849 of file CpModelProto.java.
◆ getObjectiveBuilder()
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inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 1941 of file CpModelProto.java.
◆ getObjectiveOrBuilder()
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inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Implements CpModelProtoOrBuilder.
Definition at line 1953 of file CpModelProto.java.
◆ getSearchStrategy()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements CpModelProtoOrBuilder.
Definition at line 2053 of file CpModelProto.java.
◆ getSearchStrategyBuilder()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2316 of file CpModelProto.java.
◆ getSearchStrategyBuilderList()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2420 of file CpModelProto.java.
◆ getSearchStrategyCount()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements CpModelProtoOrBuilder.
Definition at line 2031 of file CpModelProto.java.
◆ getSearchStrategyList()
|
inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements CpModelProtoOrBuilder.
Definition at line 2009 of file CpModelProto.java.
◆ getSearchStrategyOrBuilder()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements CpModelProtoOrBuilder.
Definition at line 2335 of file CpModelProto.java.
◆ getSearchStrategyOrBuilderList()
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inline |
Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements CpModelProtoOrBuilder.
Definition at line 2358 of file CpModelProto.java.
◆ getSolutionHint()
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inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
- Returns
- The solutionHint.
Implements CpModelProtoOrBuilder.
Definition at line 2476 of file CpModelProto.java.
◆ getSolutionHintBuilder()
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inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Definition at line 2608 of file CpModelProto.java.
◆ getSolutionHintOrBuilder()
|
inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Implements CpModelProtoOrBuilder.
Definition at line 2628 of file CpModelProto.java.
◆ getVariables()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements CpModelProtoOrBuilder.
Definition at line 1322 of file CpModelProto.java.
◆ getVariablesBuilder()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1505 of file CpModelProto.java.
◆ getVariablesBuilderList()
|
inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1569 of file CpModelProto.java.
◆ getVariablesCount()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements CpModelProtoOrBuilder.
Definition at line 1308 of file CpModelProto.java.
◆ getVariablesList()
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inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements CpModelProtoOrBuilder.
Definition at line 1294 of file CpModelProto.java.
◆ getVariablesOrBuilder()
|
inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements CpModelProtoOrBuilder.
Definition at line 1516 of file CpModelProto.java.
◆ getVariablesOrBuilderList()
|
inline |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements CpModelProtoOrBuilder.
Definition at line 1531 of file CpModelProto.java.
◆ hasObjective()
|
inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
- Returns
- Whether the objective field is set.
Implements CpModelProtoOrBuilder.
Definition at line 1838 of file CpModelProto.java.
◆ hasSolutionHint()
|
inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
- Returns
- Whether the solutionHint field is set.
Implements CpModelProtoOrBuilder.
Definition at line 2457 of file CpModelProto.java.
◆ internalGetFieldAccessorTable()
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inlineprotected |
Definition at line 872 of file CpModelProto.java.
◆ isInitialized()
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inline |
Definition at line 1155 of file CpModelProto.java.
◆ mergeFrom() [1/3]
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inline |
Definition at line 1049 of file CpModelProto.java.
◆ mergeFrom() [2/3]
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inline |
Definition at line 1160 of file CpModelProto.java.
◆ mergeFrom() [3/3]
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inline |
Definition at line 1040 of file CpModelProto.java.
◆ mergeObjective()
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inline |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 1901 of file CpModelProto.java.
◆ mergeSolutionHint()
|
inline |
Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Definition at line 2552 of file CpModelProto.java.
◆ mergeUnknownFields()
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inline |
Definition at line 2848 of file CpModelProto.java.
◆ removeConstraints()
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inline |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1752 of file CpModelProto.java.
◆ removeSearchStrategy()
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Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2291 of file CpModelProto.java.
◆ removeVariables()
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The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1488 of file CpModelProto.java.
◆ setAssumptions()
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A list of literals. The model will be solved assuming all these literals are true. Compared to just fixing the domain of these literals, using this mechanism is slower but allows in case the model is INFEASIBLE to get a potentially small subset of them that can be used to explain the infeasibility. Think (IIS), except when you are only concerned by the provided assumptions. This is powerful as it allows to group a set of logicially related constraint under only one enforcement literal which can potentially give you a good and interpretable explanation for infeasiblity. Such infeasibility explanation will be available in the sufficient_assumptions_for_infeasibility response field.
repeated int32 assumptions = 7;
- Parameters
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index The index to set the value at. value The assumptions to set.
- Returns
- This builder for chaining.
Definition at line 2758 of file CpModelProto.java.
◆ setConstraints() [1/2]
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repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1632 of file CpModelProto.java.
◆ setConstraints() [2/2]
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repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1649 of file CpModelProto.java.
◆ setField()
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Definition at line 1012 of file CpModelProto.java.
◆ setName()
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For debug/logging only. Can be empty.
string name = 1;
- Parameters
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value The name to set.
- Returns
- This builder for chaining.
Definition at line 1230 of file CpModelProto.java.
◆ setNameBytes()
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For debug/logging only. Can be empty.
string name = 1;
- Parameters
-
value The bytes for name to set.
- Returns
- This builder for chaining.
Definition at line 1263 of file CpModelProto.java.
◆ setObjective() [1/2]
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The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 1863 of file CpModelProto.java.
◆ setObjective() [2/2]
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The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 1883 of file CpModelProto.java.
◆ setRepeatedField()
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Definition at line 1028 of file CpModelProto.java.
◆ setSearchStrategy() [1/2]
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Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2075 of file CpModelProto.java.
◆ setSearchStrategy() [2/2]
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Defines the strategy that the solver should follow when the search_branching parameter is set to FIXED_SEARCH. Note that this strategy is also used as a heuristic when we are not in fixed search. Advanced Usage: if not all variables appears and the parameter "instantiate_all_variables" is set to false, then the solver will not try to instantiate the variables that do not appear. Thus, at the end of the search, not all variables may be fixed and this is why we have the solution_lower_bounds and solution_upper_bounds fields in the CpSolverResponse.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2104 of file CpModelProto.java.
◆ setSolutionHint() [1/2]
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Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Definition at line 2498 of file CpModelProto.java.
◆ setSolutionHint() [2/2]
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Solution hint. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. The solver will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions.
.operations_research.sat.PartialVariableAssignment solution_hint = 6;
Definition at line 2526 of file CpModelProto.java.
◆ setUnknownFields()
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Definition at line 2842 of file CpModelProto.java.
◆ setVariables() [1/2]
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The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1336 of file CpModelProto.java.
◆ setVariables() [2/2]
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The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1357 of file CpModelProto.java.
The documentation for this class was generated from the following file: