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Google OR-Tools v9.9
a fast and portable software suite for combinatorial optimization
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Google OR-Tools v9.9
a fast and portable software suite for combinatorial optimization
|
Static Public Member Functions | |
| static final com.google.protobuf.Descriptors.Descriptor | getDescriptor () |
Protected Member Functions | |
| com.google.protobuf.GeneratedMessageV3.FieldAccessorTable | internalGetFieldAccessorTable () |
A constraint programming problem.
Protobuf type operations_research.sat.CpModelProto
Definition at line 904 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addAllAssumptions | ( | java.lang.Iterable<? extends java.lang.Integer > | values | ) |
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 logically 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;
| values | The assumptions to add. |
Definition at line 3299 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addAllConstraints | ( | java.lang.Iterable<? extends com.google.ortools.sat.ConstraintProto > | values | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1911 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addAllSearchStrategy | ( | java.lang.Iterable<? extends com.google.ortools.sat.DecisionStrategyProto > | values | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2693 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addAllVariables | ( | java.lang.Iterable<? extends com.google.ortools.sat.IntegerVariableProto > | values | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1639 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addAssumptions | ( | int | value | ) |
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 logically 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;
| value | The assumptions to add. |
Definition at line 3270 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addConstraints | ( | com.google.ortools.sat.ConstraintProto | value | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1850 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addConstraints | ( | com.google.ortools.sat.ConstraintProto.Builder | builderForValue | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1883 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addConstraints | ( | int | index, |
| com.google.ortools.sat.ConstraintProto | value ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1866 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addConstraints | ( | int | index, |
| com.google.ortools.sat.ConstraintProto.Builder | builderForValue ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1897 of file CpModelProto.java.
| com.google.ortools.sat.ConstraintProto.Builder com.google.ortools.sat.CpModelProto.Builder.addConstraintsBuilder | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1980 of file CpModelProto.java.
| com.google.ortools.sat.ConstraintProto.Builder com.google.ortools.sat.CpModelProto.Builder.addConstraintsBuilder | ( | int | index | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1987 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addRepeatedField | ( | com.google.protobuf.Descriptors.FieldDescriptor | field, |
| java.lang.Object | value ) |
Definition at line 1116 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategy | ( | com.google.ortools.sat.DecisionStrategyProto | value | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2584 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategy | ( | com.google.ortools.sat.DecisionStrategyProto.Builder | builderForValue | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2641 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategy | ( | int | index, |
| com.google.ortools.sat.DecisionStrategyProto | value ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2612 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategy | ( | int | index, |
| com.google.ortools.sat.DecisionStrategyProto.Builder | builderForValue ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2667 of file CpModelProto.java.
| com.google.ortools.sat.DecisionStrategyProto.Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategyBuilder | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2834 of file CpModelProto.java.
| com.google.ortools.sat.DecisionStrategyProto.Builder com.google.ortools.sat.CpModelProto.Builder.addSearchStrategyBuilder | ( | int | index | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2853 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addVariables | ( | com.google.ortools.sat.IntegerVariableProto | value | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1562 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addVariables | ( | com.google.ortools.sat.IntegerVariableProto.Builder | builderForValue | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1603 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addVariables | ( | int | index, |
| com.google.ortools.sat.IntegerVariableProto | value ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1582 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.addVariables | ( | int | index, |
| com.google.ortools.sat.IntegerVariableProto.Builder | builderForValue ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1621 of file CpModelProto.java.
| com.google.ortools.sat.IntegerVariableProto.Builder com.google.ortools.sat.CpModelProto.Builder.addVariablesBuilder | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1732 of file CpModelProto.java.
| com.google.ortools.sat.IntegerVariableProto.Builder com.google.ortools.sat.CpModelProto.Builder.addVariablesBuilder | ( | int | index | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1743 of file CpModelProto.java.
| com.google.ortools.sat.CpModelProto com.google.ortools.sat.CpModelProto.Builder.build | ( | ) |
Definition at line 1005 of file CpModelProto.java.
| com.google.ortools.sat.CpModelProto com.google.ortools.sat.CpModelProto.Builder.buildPartial | ( | ) |
Definition at line 1014 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clear | ( | ) |
Definition at line 944 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearAssumptions | ( | ) |
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 logically 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;
Definition at line 3328 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearConstraints | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1926 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearField | ( | com.google.protobuf.Descriptors.FieldDescriptor | field | ) |
Definition at line 1100 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearFloatingPointObjective | ( | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Definition at line 2342 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearName | ( | ) |
For debug/logging only. Can be empty.
string name = 1;
Definition at line 1437 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearObjective | ( | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 2113 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearOneof | ( | com.google.protobuf.Descriptors.OneofDescriptor | oneof | ) |
Definition at line 1105 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearSearchStrategy | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2720 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearSolutionHint | ( | ) |
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 3051 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearSymmetry | ( | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Definition at line 3458 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clearVariables | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1658 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.clone | ( | ) |
Definition at line 1090 of file CpModelProto.java.
| int com.google.ortools.sat.CpModelProto.Builder.getAssumptions | ( | int | index | ) |
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 logically 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;
| index | The index of the element to return. |
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3215 of file CpModelProto.java.
| int com.google.ortools.sat.CpModelProto.Builder.getAssumptionsCount | ( | ) |
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 logically 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;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3191 of file CpModelProto.java.
| java.util.List< java.lang.Integer > com.google.ortools.sat.CpModelProto.Builder.getAssumptionsList | ( | ) |
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 logically 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;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3167 of file CpModelProto.java.
| com.google.ortools.sat.ConstraintProto com.google.ortools.sat.CpModelProto.Builder.getConstraints | ( | int | index | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1809 of file CpModelProto.java.
| com.google.ortools.sat.ConstraintProto.Builder com.google.ortools.sat.CpModelProto.Builder.getConstraintsBuilder | ( | int | index | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1952 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.ConstraintProto.Builder > com.google.ortools.sat.CpModelProto.Builder.getConstraintsBuilderList | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1996 of file CpModelProto.java.
| int com.google.ortools.sat.CpModelProto.Builder.getConstraintsCount | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1799 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.ConstraintProto > com.google.ortools.sat.CpModelProto.Builder.getConstraintsList | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1789 of file CpModelProto.java.
| com.google.ortools.sat.ConstraintProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getConstraintsOrBuilder | ( | int | index | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1959 of file CpModelProto.java.
| java.util.List<? extends com.google.ortools.sat.ConstraintProtoOrBuilder > com.google.ortools.sat.CpModelProto.Builder.getConstraintsOrBuilderList | ( | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1970 of file CpModelProto.java.
| com.google.ortools.sat.CpModelProto com.google.ortools.sat.CpModelProto.Builder.getDefaultInstanceForType | ( | ) |
Definition at line 1000 of file CpModelProto.java.
|
static |
Definition at line 909 of file CpModelProto.java.
| com.google.protobuf.Descriptors.Descriptor com.google.ortools.sat.CpModelProto.Builder.getDescriptorForType | ( | ) |
Definition at line 995 of file CpModelProto.java.
| com.google.ortools.sat.FloatObjectiveProto com.google.ortools.sat.CpModelProto.Builder.getFloatingPointObjective | ( | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2217 of file CpModelProto.java.
| com.google.ortools.sat.FloatObjectiveProto.Builder com.google.ortools.sat.CpModelProto.Builder.getFloatingPointObjectiveBuilder | ( | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Definition at line 2371 of file CpModelProto.java.
| com.google.ortools.sat.FloatObjectiveProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getFloatingPointObjectiveOrBuilder | ( | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2395 of file CpModelProto.java.
| java.lang.String com.google.ortools.sat.CpModelProto.Builder.getName | ( | ) |
For debug/logging only. Can be empty.
string name = 1;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1379 of file CpModelProto.java.
| com.google.protobuf.ByteString com.google.ortools.sat.CpModelProto.Builder.getNameBytes | ( | ) |
For debug/logging only. Can be empty.
string name = 1;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1400 of file CpModelProto.java.
| com.google.ortools.sat.CpObjectiveProto com.google.ortools.sat.CpModelProto.Builder.getObjective | ( | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2036 of file CpModelProto.java.
| com.google.ortools.sat.CpObjectiveProto.Builder com.google.ortools.sat.CpModelProto.Builder.getObjectiveBuilder | ( | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 2130 of file CpModelProto.java.
| com.google.ortools.sat.CpObjectiveProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getObjectiveOrBuilder | ( | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2142 of file CpModelProto.java.
| com.google.ortools.sat.DecisionStrategyProto com.google.ortools.sat.CpModelProto.Builder.getSearchStrategy | ( | int | index | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2507 of file CpModelProto.java.
| com.google.ortools.sat.DecisionStrategyProto.Builder com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyBuilder | ( | int | index | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2770 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.DecisionStrategyProto.Builder > com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyBuilderList | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2874 of file CpModelProto.java.
| int com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyCount | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2485 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.DecisionStrategyProto > com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyList | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2463 of file CpModelProto.java.
| com.google.ortools.sat.DecisionStrategyProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyOrBuilder | ( | int | index | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2789 of file CpModelProto.java.
| java.util.List<? extends com.google.ortools.sat.DecisionStrategyProtoOrBuilder > com.google.ortools.sat.CpModelProto.Builder.getSearchStrategyOrBuilderList | ( | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2812 of file CpModelProto.java.
| com.google.ortools.sat.PartialVariableAssignment com.google.ortools.sat.CpModelProto.Builder.getSolutionHint | ( | ) |
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 com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2934 of file CpModelProto.java.
| com.google.ortools.sat.PartialVariableAssignment.Builder com.google.ortools.sat.CpModelProto.Builder.getSolutionHintBuilder | ( | ) |
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 3078 of file CpModelProto.java.
| com.google.ortools.sat.PartialVariableAssignmentOrBuilder com.google.ortools.sat.CpModelProto.Builder.getSolutionHintOrBuilder | ( | ) |
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 com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3100 of file CpModelProto.java.
| com.google.ortools.sat.SymmetryProto com.google.ortools.sat.CpModelProto.Builder.getSymmetry | ( | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3365 of file CpModelProto.java.
| com.google.ortools.sat.SymmetryProto.Builder com.google.ortools.sat.CpModelProto.Builder.getSymmetryBuilder | ( | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Definition at line 3479 of file CpModelProto.java.
| com.google.ortools.sat.SymmetryProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getSymmetryOrBuilder | ( | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3495 of file CpModelProto.java.
| com.google.ortools.sat.IntegerVariableProto com.google.ortools.sat.CpModelProto.Builder.getVariables | ( | int | index | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1509 of file CpModelProto.java.
| com.google.ortools.sat.IntegerVariableProto.Builder com.google.ortools.sat.CpModelProto.Builder.getVariablesBuilder | ( | int | index | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1692 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.IntegerVariableProto.Builder > com.google.ortools.sat.CpModelProto.Builder.getVariablesBuilderList | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1756 of file CpModelProto.java.
| int com.google.ortools.sat.CpModelProto.Builder.getVariablesCount | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1495 of file CpModelProto.java.
| java.util.List< com.google.ortools.sat.IntegerVariableProto > com.google.ortools.sat.CpModelProto.Builder.getVariablesList | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1481 of file CpModelProto.java.
| com.google.ortools.sat.IntegerVariableProtoOrBuilder com.google.ortools.sat.CpModelProto.Builder.getVariablesOrBuilder | ( | int | index | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1703 of file CpModelProto.java.
| java.util.List<? extends com.google.ortools.sat.IntegerVariableProtoOrBuilder > com.google.ortools.sat.CpModelProto.Builder.getVariablesOrBuilderList | ( | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 1718 of file CpModelProto.java.
| boolean com.google.ortools.sat.CpModelProto.Builder.hasFloatingPointObjective | ( | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2194 of file CpModelProto.java.
| boolean com.google.ortools.sat.CpModelProto.Builder.hasObjective | ( | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2025 of file CpModelProto.java.
| boolean com.google.ortools.sat.CpModelProto.Builder.hasSolutionHint | ( | ) |
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 com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 2913 of file CpModelProto.java.
| boolean com.google.ortools.sat.CpModelProto.Builder.hasSymmetry | ( | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Implements com.google.ortools.sat.CpModelProtoOrBuilder.
Definition at line 3350 of file CpModelProto.java.
|
protected |
Definition at line 915 of file CpModelProto.java.
| final boolean com.google.ortools.sat.CpModelProto.Builder.isInitialized | ( | ) |
Definition at line 1245 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeFloatingPointObjective | ( | com.google.ortools.sat.FloatObjectiveProto | value | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Definition at line 2305 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeFrom | ( | com.google.ortools.sat.CpModelProto | other | ) |
Definition at line 1131 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeFrom | ( | com.google.protobuf.CodedInputStream | input, |
| com.google.protobuf.ExtensionRegistryLite | extensionRegistry ) throws java.io.IOException |
Definition at line 1250 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeFrom | ( | com.google.protobuf.Message | other | ) |
Definition at line 1122 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeObjective | ( | com.google.ortools.sat.CpObjectiveProto | value | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 2088 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeSolutionHint | ( | com.google.ortools.sat.PartialVariableAssignment | value | ) |
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 3016 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.mergeSymmetry | ( | com.google.ortools.sat.SymmetryProto | value | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Definition at line 3429 of file CpModelProto.java.
| final Builder com.google.ortools.sat.CpModelProto.Builder.mergeUnknownFields | ( | final com.google.protobuf.UnknownFieldSet | unknownFields | ) |
Definition at line 3534 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.removeConstraints | ( | int | index | ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1939 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.removeSearchStrategy | ( | int | index | ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2745 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.removeVariables | ( | int | index | ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1675 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setAssumptions | ( | int | index, |
| int | value ) |
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 logically 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;
| index | The index to set the value at. |
| value | The assumptions to set. |
Definition at line 3240 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setConstraints | ( | int | index, |
| com.google.ortools.sat.ConstraintProto | value ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1819 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setConstraints | ( | int | index, |
| com.google.ortools.sat.ConstraintProto.Builder | builderForValue ) |
repeated .operations_research.sat.ConstraintProto constraints = 3;
Definition at line 1836 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setField | ( | com.google.protobuf.Descriptors.FieldDescriptor | field, |
| java.lang.Object | value ) |
Definition at line 1094 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setFloatingPointObjective | ( | com.google.ortools.sat.FloatObjectiveProto | value | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Definition at line 2243 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setFloatingPointObjective | ( | com.google.ortools.sat.FloatObjectiveProto.Builder | builderForValue | ) |
Advanced usage. It is invalid to have both an objective and a floating point objective. The objective of the model, in floating point format. The solver will automatically scale this to integer during expansion and thus convert it to a normal CpObjectiveProto. See the mip* parameters to control how this is scaled. In most situation the precision will be good enough, but you can see the logs to see what are the precision guaranteed when this is converted to a fixed point representation. Note that even if the precision is bad, the returned objective_value and best_objective_bound will be computed correctly. So at the end of the solve you can check the gap if you only want precise optimal.
.operations_research.sat.FloatObjectiveProto floating_point_objective = 9;
Definition at line 2275 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setName | ( | java.lang.String | value | ) |
For debug/logging only. Can be empty.
string name = 1;
| value | The name to set. |
Definition at line 1421 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setNameBytes | ( | com.google.protobuf.ByteString | value | ) |
For debug/logging only. Can be empty.
string name = 1;
| value | The bytes for name to set. |
Definition at line 1452 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setObjective | ( | com.google.ortools.sat.CpObjectiveProto | value | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 2050 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setObjective | ( | com.google.ortools.sat.CpObjectiveProto.Builder | builderForValue | ) |
The objective to minimize. Can be empty for pure decision problems.
.operations_research.sat.CpObjectiveProto objective = 4;
Definition at line 2070 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setRepeatedField | ( | com.google.protobuf.Descriptors.FieldDescriptor | field, |
| int | index, | ||
| java.lang.Object | value ) |
Definition at line 1110 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSearchStrategy | ( | int | index, |
| com.google.ortools.sat.DecisionStrategyProto | value ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2529 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSearchStrategy | ( | int | index, |
| com.google.ortools.sat.DecisionStrategyProto.Builder | builderForValue ) |
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. Currently, we will set them to their lower bound in the solution.
repeated .operations_research.sat.DecisionStrategyProto search_strategy = 5;
Definition at line 2558 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSolutionHint | ( | com.google.ortools.sat.PartialVariableAssignment | value | ) |
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 2958 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSolutionHint | ( | com.google.ortools.sat.PartialVariableAssignment.Builder | builderForValue | ) |
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 2988 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSymmetry | ( | com.google.ortools.sat.SymmetryProto | value | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Definition at line 3383 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setSymmetry | ( | com.google.ortools.sat.SymmetryProto.Builder | builderForValue | ) |
For now, this is not meant to be filled by a client writing a model, but by our preprocessing step. Information about the symmetries of the feasible solution space. These usually leaves the objective invariant.
.operations_research.sat.SymmetryProto symmetry = 8;
Definition at line 3407 of file CpModelProto.java.
| final Builder com.google.ortools.sat.CpModelProto.Builder.setUnknownFields | ( | final com.google.protobuf.UnknownFieldSet | unknownFields | ) |
Definition at line 3528 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setVariables | ( | int | index, |
| com.google.ortools.sat.IntegerVariableProto | value ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1523 of file CpModelProto.java.
| Builder com.google.ortools.sat.CpModelProto.Builder.setVariables | ( | int | index, |
| com.google.ortools.sat.IntegerVariableProto.Builder | builderForValue ) |
The associated Protos should be referred by their index in these fields.
repeated .operations_research.sat.IntegerVariableProto variables = 2;
Definition at line 1544 of file CpModelProto.java.
1.10.0