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

  • Method Details

    • 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.