![]() |
Google OR-Tools v9.12
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.GeneratedMessage.FieldAccessorTable | internalGetFieldAccessorTable () |
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 operations_research.MPSolverCommonParameters
Definition at line 719 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.MPSolverCommonParameters com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.build | ( | ) |
Definition at line 791 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.MPSolverCommonParameters com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.buildPartial | ( | ) |
Definition at line 800 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clear | ( | ) |
Definition at line 755 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearDualTolerance | ( | ) |
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 1563 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearLpAlgorithm | ( | ) |
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];
Definition at line 1688 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearPresolve | ( | ) |
Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
Definition at line 1750 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearPrimalTolerance | ( | ) |
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 1373 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearRelativeMipGap | ( | ) |
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 1156 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.clearScaling | ( | ) |
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];
Definition at line 1816 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.MPSolverCommonParameters com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getDefaultInstanceForType | ( | ) |
Definition at line 786 of file MPSolverCommonParameters.java.
|
static |
Definition at line 724 of file MPSolverCommonParameters.java.
com.google.protobuf.Descriptors.Descriptor com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getDescriptorForType | ( | ) |
Definition at line 781 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1470 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble.Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getDualToleranceBuilder | ( | ) |
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 1584 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDoubleOrBuilder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1600 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.MPSolverCommonParameters.LPAlgorithmValues com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1656 of file MPSolverCommonParameters.java.
com.google.ortools.util.OptionalBoolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getPresolve | ( | ) |
Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1718 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1284 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble.Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getPrimalToleranceBuilder | ( | ) |
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 1393 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDoubleOrBuilder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1408 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1023 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDouble.Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.getRelativeMipGapBuilder | ( | ) |
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 1187 of file MPSolverCommonParameters.java.
com.google.ortools.linearsolver.OptionalDoubleOrBuilder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1213 of file MPSolverCommonParameters.java.
com.google.ortools.util.OptionalBoolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1782 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1455 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1643 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.hasPresolve | ( | ) |
Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1705 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1270 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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;
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 998 of file MPSolverCommonParameters.java.
boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.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];
Implements com.google.ortools.linearsolver.MPSolverCommonParametersOrBuilder.
Definition at line 1768 of file MPSolverCommonParameters.java.
|
protected |
Definition at line 730 of file MPSolverCommonParameters.java.
final boolean com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.isInitialized | ( | ) |
Definition at line 879 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergeDualTolerance | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1534 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergeFrom | ( | com.google.ortools.linearsolver.MPSolverCommonParameters | other | ) |
Definition at line 853 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergeFrom | ( | com.google.protobuf.CodedInputStream | input, |
com.google.protobuf.ExtensionRegistryLite | extensionRegistry ) throws java.io.IOException |
Definition at line 884 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergeFrom | ( | com.google.protobuf.Message | other | ) |
Definition at line 844 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergePrimalTolerance | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1345 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.mergeRelativeMipGap | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1117 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setDualTolerance | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1488 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setDualTolerance | ( | com.google.ortools.linearsolver.OptionalDouble.Builder | builderForValue | ) |
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 1512 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setLpAlgorithm | ( | com.google.ortools.linearsolver.MPSolverCommonParameters.LPAlgorithmValues | value | ) |
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];
value | The lpAlgorithm to set. |
Definition at line 1670 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setPresolve | ( | com.google.ortools.util.OptionalBoolean | value | ) |
Gurobi and SCIP enable presolve by default. Ask or-core-team@ for other solvers.
optional .operations_research.OptionalBoolean presolve = 5 [default = BOOL_UNSPECIFIED];
value | The presolve to set. |
Definition at line 1732 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setPrimalTolerance | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1301 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setPrimalTolerance | ( | com.google.ortools.linearsolver.OptionalDouble.Builder | builderForValue | ) |
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 1324 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setRelativeMipGap | ( | com.google.ortools.linearsolver.OptionalDouble | value | ) |
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 1051 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setRelativeMipGap | ( | com.google.ortools.linearsolver.OptionalDouble.Builder | builderForValue | ) |
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 1085 of file MPSolverCommonParameters.java.
Builder com.google.ortools.linearsolver.MPSolverCommonParameters.Builder.setScaling | ( | com.google.ortools.util.OptionalBoolean | value | ) |
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];
value | The scaling to set. |
Definition at line 1797 of file MPSolverCommonParameters.java.