Java Reference
Java Reference
Detailed Description
MPSolverCommonParameters holds advanced usage parameters that apply to any of the solvers we support. All of the fields in this proto can have a value of unspecified. In this case each inner solver will use their own safe defaults. Some values won't be supported by some solvers. The behavior in that case is not defined yet.
Protobuf type
Definition at line 819 of file MPSolverCommonParameters.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
◆ addRepeatedField()
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Definition at line 977 of file MPSolverCommonParameters.java.
◆ build()
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Definition at line 896 of file MPSolverCommonParameters.java.
◆ buildPartial()
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Definition at line 905 of file MPSolverCommonParameters.java.
◆ clear()
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Definition at line 855 of file MPSolverCommonParameters.java.
◆ clearDualTolerance()
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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;
Definition at line 1611 of file MPSolverCommonParameters.java.
◆ clearField()
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Definition at line 961 of file MPSolverCommonParameters.java.
◆ clearLpAlgorithm()
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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
- This builder for chaining.
Definition at line 1737 of file MPSolverCommonParameters.java.
◆ clearOneof()
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Definition at line 966 of file MPSolverCommonParameters.java.
◆ clearPresolve()
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Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
- Returns
- This builder for chaining.
Definition at line 1800 of file MPSolverCommonParameters.java.
◆ clearPrimalTolerance()
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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;
Definition at line 1422 of file MPSolverCommonParameters.java.
◆ clearRelativeMipGap()
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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;
Definition at line 1212 of file MPSolverCommonParameters.java.
◆ clearScaling()
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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
- This builder for chaining.
Definition at line 1867 of file MPSolverCommonParameters.java.
◆ clone()
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Definition at line 951 of file MPSolverCommonParameters.java.
◆ getDefaultInstanceForType()
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Definition at line 891 of file MPSolverCommonParameters.java.
◆ getDescriptor()
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Definition at line 824 of file MPSolverCommonParameters.java.
◆ getDescriptorForType()
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Definition at line 886 of file MPSolverCommonParameters.java.
◆ getDualTolerance()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1519 of file MPSolverCommonParameters.java.
◆ getDualToleranceBuilder()
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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;
Definition at line 1632 of file MPSolverCommonParameters.java.
◆ getDualToleranceOrBuilder()
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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;
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1648 of file MPSolverCommonParameters.java.
◆ getLpAlgorithm()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1704 of file MPSolverCommonParameters.java.
◆ getPresolve()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1767 of file MPSolverCommonParameters.java.
◆ getPrimalTolerance()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1334 of file MPSolverCommonParameters.java.
◆ getPrimalToleranceBuilder()
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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;
Definition at line 1442 of file MPSolverCommonParameters.java.
◆ getPrimalToleranceOrBuilder()
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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;
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1457 of file MPSolverCommonParameters.java.
◆ getRelativeMipGap()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1088 of file MPSolverCommonParameters.java.
◆ getRelativeMipGapBuilder()
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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;
Definition at line 1241 of file MPSolverCommonParameters.java.
◆ getRelativeMipGapOrBuilder()
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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;
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1265 of file MPSolverCommonParameters.java.
◆ getScaling()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1832 of file MPSolverCommonParameters.java.
◆ hasDualTolerance()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1504 of file MPSolverCommonParameters.java.
◆ hasLpAlgorithm()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1691 of file MPSolverCommonParameters.java.
◆ hasPresolve()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1754 of file MPSolverCommonParameters.java.
◆ hasPrimalTolerance()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1320 of file MPSolverCommonParameters.java.
◆ hasRelativeMipGap()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1065 of file MPSolverCommonParameters.java.
◆ hasScaling()
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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.
Implements MPSolverCommonParametersOrBuilder.
Definition at line 1818 of file MPSolverCommonParameters.java.
◆ internalGetFieldAccessorTable()
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Definition at line 830 of file MPSolverCommonParameters.java.
◆ isInitialized()
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Definition at line 1018 of file MPSolverCommonParameters.java.
◆ mergeDualTolerance()
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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;
Definition at line 1583 of file MPSolverCommonParameters.java.
◆ mergeFrom() [1/3]
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Definition at line 992 of file MPSolverCommonParameters.java.
◆ mergeFrom() [2/3]
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Definition at line 1023 of file MPSolverCommonParameters.java.
◆ mergeFrom() [3/3]
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Definition at line 983 of file MPSolverCommonParameters.java.
◆ mergePrimalTolerance()
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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;
Definition at line 1395 of file MPSolverCommonParameters.java.
◆ mergeRelativeMipGap()
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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;
Definition at line 1176 of file MPSolverCommonParameters.java.
◆ mergeUnknownFields()
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Definition at line 1880 of file MPSolverCommonParameters.java.
◆ setDualTolerance() [1/2]
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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;
Definition at line 1537 of file MPSolverCommonParameters.java.
◆ setDualTolerance() [2/2]
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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;
Definition at line 1561 of file MPSolverCommonParameters.java.
◆ setField()
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Definition at line 955 of file MPSolverCommonParameters.java.
◆ setLpAlgorithm()
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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];
- Parameters
-
value The lpAlgorithm to set.
- Returns
- This builder for chaining.
Definition at line 1719 of file MPSolverCommonParameters.java.
◆ setPresolve()
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Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
- Parameters
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value The presolve to set.
- Returns
- This builder for chaining.
Definition at line 1782 of file MPSolverCommonParameters.java.
◆ setPrimalTolerance() [1/2]
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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;
Definition at line 1351 of file MPSolverCommonParameters.java.
◆ setPrimalTolerance() [2/2]
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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;
Definition at line 1374 of file MPSolverCommonParameters.java.
◆ setRelativeMipGap() [1/2]
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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;
Definition at line 1114 of file MPSolverCommonParameters.java.
◆ setRelativeMipGap() [2/2]
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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;
Definition at line 1146 of file MPSolverCommonParameters.java.
◆ setRepeatedField()
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Definition at line 971 of file MPSolverCommonParameters.java.
◆ setScaling()
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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];
- Parameters
-
value The scaling to set.
- Returns
- This builder for chaining.
Definition at line 1848 of file MPSolverCommonParameters.java.
◆ setUnknownFields()
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Definition at line 1874 of file MPSolverCommonParameters.java.
The documentation for this class was generated from the following file: