com.google.ortools.linearsolver

Interface MPSolverCommonParametersOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

MPSolverCommonParameters, MPSolverCommonParameters.Builder

public interface MPSolverCommonParametersOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
OptionalDouble	getDualTolerance() Tolerance for dual feasibility.
OptionalDoubleOrBuilder	getDualToleranceOrBuilder() Tolerance for dual feasibility.
MPSolverCommonParameters.LPAlgorithmValues	getLpAlgorithm() Algorithm to solve linear programs.
OptionalBoolean	getPresolve() Gurobi and SCIP enable presolve by default.
OptionalDouble	getPrimalTolerance() Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.
OptionalDoubleOrBuilder	getPrimalToleranceOrBuilder() Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.
OptionalDouble	getRelativeMipGap() The solver stops if the relative MIP gap reaches this value or below.
OptionalDoubleOrBuilder	getRelativeMipGapOrBuilder() The solver stops if the relative MIP gap reaches this value or below.
OptionalBoolean	getScaling() Enable automatic scaling of matrix coefficients and objective.
boolean	hasDualTolerance() Tolerance for dual feasibility.
boolean	hasLpAlgorithm() Algorithm to solve linear programs.
boolean	hasPresolve() Gurobi and SCIP enable presolve by default.
boolean	hasPrimalTolerance() Tolerance for primal feasibility of basic solutions: this is the maximum allowed error in constraint satisfiability.
boolean	hasRelativeMipGap() The solver stops if the relative MIP gap reaches this value or below.
boolean	hasScaling() Enable automatic scaling of matrix coefficients and objective.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

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.

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.

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;

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.

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.

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;

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.

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.

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;

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.

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.

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.

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.

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.

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.