Interface MPSolverCommonParametersOrBuilder
- All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder
,com.google.protobuf.MessageOrBuilder
- All Known Implementing Classes:
MPSolverCommonParameters
,MPSolverCommonParameters.Builder
@Generated
public interface MPSolverCommonParametersOrBuilder
extends com.google.protobuf.MessageOrBuilder
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Method Summary
Modifier and TypeMethodDescriptionTolerance for dual feasibility.Tolerance for dual feasibility.Algorithm to solve linear programs.Gurobi and SCIP enable presolve by default.Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.The solver stops if the relative MIP gap reaches this value or below.The solver stops if the relative MIP gap reaches this value or below.Enable automatic scaling of matrix coefficients and objective.boolean
Tolerance for dual feasibility.boolean
Algorithm to solve linear programs.boolean
Gurobi and SCIP enable presolve by default.boolean
Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.boolean
The solver stops if the relative MIP gap reaches this value or below.boolean
Enable automatic scaling of matrix coefficients and objective.Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder
isInitialized
Methods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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hasRelativeMipGap
boolean hasRelativeMipGap()The solver stops if the relative MIP gap reaches this value or below. The relative MIP gap is an upper bound of the relative distance to the optimum, and it is defined as: abs(best_bound - incumbent) / abs(incumbent) [Gurobi] abs(best_bound - incumbent) / min(abs(best_bound), abs(incumbent)) [SCIP] where "incumbent" is the objective value of the best solution found so far (i.e., lowest when minimizing, highest when maximizing), and "best_bound" is the tightest bound of the objective determined so far (i.e., highest when minimizing, and lowest when maximizing). The MIP Gap is sensitive to objective offset. If the denominator is 0 the MIP Gap is INFINITY for SCIP and Gurobi. Of note, "incumbent" and "best bound" are called "primal bound" and "dual bound" in SCIP, respectively. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalDouble relative_mip_gap = 1;
- Returns:
- Whether the relativeMipGap field is set.
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getRelativeMipGap
OptionalDouble getRelativeMipGap()The solver stops if the relative MIP gap reaches this value or below. The relative MIP gap is an upper bound of the relative distance to the optimum, and it is defined as: abs(best_bound - incumbent) / abs(incumbent) [Gurobi] abs(best_bound - incumbent) / min(abs(best_bound), abs(incumbent)) [SCIP] where "incumbent" is the objective value of the best solution found so far (i.e., lowest when minimizing, highest when maximizing), and "best_bound" is the tightest bound of the objective determined so far (i.e., highest when minimizing, and lowest when maximizing). The MIP Gap is sensitive to objective offset. If the denominator is 0 the MIP Gap is INFINITY for SCIP and Gurobi. Of note, "incumbent" and "best bound" are called "primal bound" and "dual bound" in SCIP, respectively. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalDouble relative_mip_gap = 1;
- Returns:
- The relativeMipGap.
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getRelativeMipGapOrBuilder
OptionalDoubleOrBuilder getRelativeMipGapOrBuilder()The solver stops if the relative MIP gap reaches this value or below. The relative MIP gap is an upper bound of the relative distance to the optimum, and it is defined as: abs(best_bound - incumbent) / abs(incumbent) [Gurobi] abs(best_bound - incumbent) / min(abs(best_bound), abs(incumbent)) [SCIP] where "incumbent" is the objective value of the best solution found so far (i.e., lowest when minimizing, highest when maximizing), and "best_bound" is the tightest bound of the objective determined so far (i.e., highest when minimizing, and lowest when maximizing). The MIP Gap is sensitive to objective offset. If the denominator is 0 the MIP Gap is INFINITY for SCIP and Gurobi. Of note, "incumbent" and "best bound" are called "primal bound" and "dual bound" in SCIP, respectively. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalDouble relative_mip_gap = 1;
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hasPrimalTolerance
boolean hasPrimalTolerance()Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability. For SCIP this includes integrality constraints. For Gurobi it does not, you need to set the custom parameter IntFeasTol.
optional .operations_research.OptionalDouble primal_tolerance = 2;
- Returns:
- Whether the primalTolerance field is set.
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getPrimalTolerance
OptionalDouble getPrimalTolerance()Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability. For SCIP this includes integrality constraints. For Gurobi it does not, you need to set the custom parameter IntFeasTol.
optional .operations_research.OptionalDouble primal_tolerance = 2;
- Returns:
- The primalTolerance.
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getPrimalToleranceOrBuilder
OptionalDoubleOrBuilder getPrimalToleranceOrBuilder()Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability. For SCIP this includes integrality constraints. For Gurobi it does not, you need to set the custom parameter IntFeasTol.
optional .operations_research.OptionalDouble primal_tolerance = 2;
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hasDualTolerance
boolean hasDualTolerance()Tolerance for dual feasibility. For SCIP and Gurobi this is the feasibility tolerance for reduced costs in LP solution: reduced costs must all be smaller than this value in the improving direction in order for a model to be declared optimal. Not supported for other solvers.
optional .operations_research.OptionalDouble dual_tolerance = 3;
- Returns:
- Whether the dualTolerance field is set.
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getDualTolerance
OptionalDouble getDualTolerance()Tolerance for dual feasibility. For SCIP and Gurobi this is the feasibility tolerance for reduced costs in LP solution: reduced costs must all be smaller than this value in the improving direction in order for a model to be declared optimal. Not supported for other solvers.
optional .operations_research.OptionalDouble dual_tolerance = 3;
- Returns:
- The dualTolerance.
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getDualToleranceOrBuilder
OptionalDoubleOrBuilder getDualToleranceOrBuilder()Tolerance for dual feasibility. For SCIP and Gurobi this is the feasibility tolerance for reduced costs in LP solution: reduced costs must all be smaller than this value in the improving direction in order for a model to be declared optimal. Not supported for other solvers.
optional .operations_research.OptionalDouble dual_tolerance = 3;
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hasLpAlgorithm
boolean hasLpAlgorithm()Algorithm to solve linear programs. Ask or-core-team@ if you want to know what this does exactly.
optional .operations_research.MPSolverCommonParameters.LPAlgorithmValues lp_algorithm = 4 [default = LP_ALGO_UNSPECIFIED];
- Returns:
- Whether the lpAlgorithm field is set.
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getLpAlgorithm
MPSolverCommonParameters.LPAlgorithmValues getLpAlgorithm()Algorithm to solve linear programs. Ask or-core-team@ if you want to know what this does exactly.
optional .operations_research.MPSolverCommonParameters.LPAlgorithmValues lp_algorithm = 4 [default = LP_ALGO_UNSPECIFIED];
- Returns:
- The lpAlgorithm.
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hasPresolve
boolean hasPresolve()Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
- Returns:
- Whether the presolve field is set.
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getPresolve
OptionalBoolean getPresolve()Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
- Returns:
- The presolve.
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hasScaling
boolean hasScaling()Enable automatic scaling of matrix coefficients and objective. Available for Gurobi and GLOP. Ask or-core-team@ if you want more details.
optional .operations_research.OptionalBoolean scaling = 7 [default = BOOL_UNSPECIFIED];
- Returns:
- Whether the scaling field is set.
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getScaling
OptionalBoolean getScaling()Enable automatic scaling of matrix coefficients and objective. Available for Gurobi and GLOP. Ask or-core-team@ if you want more details.
optional .operations_research.OptionalBoolean scaling = 7 [default = BOOL_UNSPECIFIED];
- Returns:
- The scaling.
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