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LHLHD$(1H@Ǩ^H>1OD‰>$H5]H1H1D‰$H5H]HH1NH"H"fSHH@uHHxH;= u[HHxH;= tH=; tP[DPJHf.HPy@HJyBHHAUATUHSHIHOHtBHHSHCHHH; H]HH[]A\A]Ld$@Ll$0HLHHPH$HHD$`H$HD$hPHL$`HLL)L$HLd$8HD$0HǔH$HD$$_H= =LcHSH?I9I9v HI9LBID$9H=v%L9s %II)H?I9LGI|$IHSIL`@Hu"HXL;- IUADfHHHt&HHkHSHfCsAEHSHH=$@AWIHAVAUIATIUSH(HOH/HH)H)HH<IH9LHT$HL$fHT$HL$HIIILLM)HK9HD$I9HHLL$HL$-HL$LL$I9t>LLLpHu+H\$~D$MuD$AEH([]A\A]A^A_HXfDHH95E11HIDI9u두L4f.@AWIHAVAUIATIUSH(HOH/HH)H)HH<IH9LHT$HL$HT$HL$HIAILLM)K9HD$I9HHLL$HL$HL$LL$I9t;LLLHu(H\$~D$MuD$AEH([]A\A]A^A_HfDHH95E11HIDI9u딐L4fHH 0@P0123456789abcdefSwigPyObjectunknownthis__new____swig_destroy__(, SwigPyPackedswigvarlinkExpecting str or bytesat least at most %S Additional information: %s%s%sbasic_string::_S_create_p_charstd::string *Solver_VerifySolutionObjective_SetOffsetVariable_SetIntegerVariable_SetBoundsVariable_SetLbVariable_SetUbConstraint_SetBoundsConstraint_set_is_lazyConstraint_SetLbConstraint_SetUbSolver_SolvesurrogateescapeSolver_LookupVariableSolver_VarSolver_BoolVarSolver_LookupConstraintSolver_Constraintnew_ModelExportOptionsnew_MPSolverParametersVariable_SetBranchingPrioritySolver_SetNumThreadsSolver_set_time_limitSolver_SetTimeLimitSolver_NumVarSolver_IntVarnew_SolverSolver_InfinitySolver_infinityConstraint_GetCoefficientConstraint_SetCoefficientObjective_GetCoefficientObjective_SetCoefficientswig_ptr: swig_runtime_data4type_pointer_capsuleSolver_CLP_LINEAR_PROGRAMMINGSolver_OPTIMALSolver_FEASIBLESolver_INFEASIBLESolver_UNBOUNDEDSolver_ABNORMALSolver_NOT_SOLVEDSolver_FREESolver_AT_LOWER_BOUNDSolver_AT_UPPER_BOUNDSolver_FIXED_VALUESolver_BASICMPSolverParameters_PRESOLVEMPSolverParameters_SCALINGMPSolverParameters_DUALMPSolverParameters_PRIMALMPSolverParameters_BARRIERMPSolverParameters_SCALING_ONcvar__lshift__Solver_SetHintsequence(double) expectedhint.SerializeToStringSolver_LoadModelFromProtoSolver_ExportModelToProto(O)ParseFromStringMPModelProtoSolver_ExportModelAsLpFormatSolver_ExportModelAsMpsFormatSolver_SolveWithProtoSolver_LoadSolutionFromProtoMPSolutionResponse_pywraplp_p_unsigned_short_p_unsigned_long_p_unsigned_int_p_unsigned_char_p_std__ostreamstd::ostream *_p_signed_char_p_short_p_long_p_intchar *SWIG_PyInstanceMethod_Newdelete_SolverSolver_CreateSolverSolver_SupportsProblemTypeSolver_ClearSolver_NumVariablesSolver_variables Creates an integer variable. Creates a boolean variable.Solver_NumConstraintsSolver_constraintsSolver_ObjectiveSolver_InterruptSolveSolver_EnableOutput Enables solver logging.Solver_SuppressOutput Suppresses solver logging.Solver_iterationsSolver_nodesSolver_NextSolutionSolver_wall_timeSolver_SetGurobiLibraryPathSolver_WallTimeSolver_IterationsSolver_swigregisterSolver_swiginitObjective_ClearObjective_offsetObjective_SetMinimizationObjective_SetMaximizationObjective_maximizationObjective_minimizationObjective_ValueObjective_BestBoundObjective_Offsetdelete_ObjectiveObjective_swigregisterVariable_nameVariable_integerVariable_solution_valueVariable_indexVariable_lb Returns the lower bound.Variable_ub Returns the upper bound.Variable_reduced_costVariable_basis_statusVariable_branching_priorityVariable___str__Variable___repr__Variable_SolutionValueVariable_IntegerVariable_LbVariable_UbVariable_ReducedCostdelete_VariableVariable_swigregisterConstraint_nameConstraint_ClearConstraint_lbConstraint_ubConstraint_indexConstraint_dual_valueConstraint_basis_statusConstraint_LbConstraint_UbConstraint_DualValuedelete_ConstraintConstraint_swigregisterdelete_MPSolverParametersMPSolverParameters_swiginitdelete_ModelExportOptionsModelExportOptions_swiginitFindErrorInModelProtodisownacquireappendappends another 'this' objectnextreturns object representationVariable MPSolverParameters_kDefaultIncrementality is read-only.Variable MPSolverParameters_kDefaultPresolve is read-only.Variable MPSolverParameters_kDefaultDualTolerance is read-only.Variable MPSolverParameters_kDefaultPrimalTolerance is read-only.Variable MPSolverParameters_kDefaultRelativeMipGap is read-only.swig_runtime_data4.type_pointer_capsuleUnknown C global variable '%s'%s expected %s%d arguments, got noneUnpackTuple() argument list is not a tuple%s expected %s%d arguments, got %dAttempt to append a non SwigPyObjectswig/python detected a memory leak of type '%s', no destructor found. in method 'Solver_SetGurobiLibraryPath', argument 1 of type 'std::string const &'invalid null reference in method 'Solver_SetGurobiLibraryPath', argument 1 of type 'std::string const &'in method 'Solver_Clear', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_NumVariables', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_NumConstraints', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_ComputeConstraintActivities', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_VerifySolution', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_VerifySolution', argument 2 of type 'double'in method 'Solver_VerifySolution', argument 3 of type 'bool'in method 'Solver_InterruptSolve', argument 1 of type 'operations_research::MPSolver *'Solver_SetSolverSpecificParametersAsStringin method 'Solver_SetSolverSpecificParametersAsString', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_SetSolverSpecificParametersAsString', argument 2 of type 'std::string const &'invalid null reference in method 'Solver_SetSolverSpecificParametersAsString', argument 2 of type 'std::string const &'in method 'Solver_EnableOutput', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_SuppressOutput', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_iterations', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_nodes', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_ComputeExactConditionNumber', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_NextSolution', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_wall_time', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_WallTime', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_Iterations', argument 1 of type 'operations_research::MPSolver const *'in method 'Objective_Clear', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_SetOffset', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_SetOffset', argument 2 of type 'double'in method 'Objective_offset', argument 1 of type 'operations_research::MPObjective const *'Objective_SetOptimizationDirectionin method 'Objective_SetOptimizationDirection', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_SetOptimizationDirection', argument 2 of type 'bool'in method 'Objective_SetMinimization', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_SetMaximization', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_maximization', argument 1 of type 'operations_research::MPObjective const *'in method 'Objective_minimization', argument 1 of type 'operations_research::MPObjective const *'in method 'Objective_Value', argument 1 of type 'operations_research::MPObjective const *'in method 'Objective_BestBound', argument 1 of type 'operations_research::MPObjective const *'in method 'Objective_Offset', argument 1 of type 'operations_research::MPObjective const *'in method 'Variable_SetInteger', argument 1 of type 'operations_research::MPVariable *'in method 'Variable_SetInteger', argument 2 of type 'bool'in method 'Variable_integer', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_solution_value', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_index', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_lb', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_ub', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_SetBounds', argument 1 of type 'operations_research::MPVariable *'in method 'Variable_SetBounds', argument 2 of type 'double'in method 'Variable_SetBounds', argument 3 of type 'double'in method 'Variable_reduced_cost', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_basis_status', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_branching_priority', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_SolutionValue', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_Integer', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_Lb', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_Ub', argument 1 of type 'operations_research::MPVariable const *'in method 'Variable_SetLb', argument 1 of type 'operations_research::MPVariable *'in method 'Variable_SetLb', argument 2 of type 'double'in method 'Variable_SetUb', argument 1 of type 'operations_research::MPVariable *'in method 'Variable_SetUb', argument 2 of type 'double'in method 'Variable_ReducedCost', argument 1 of type 'operations_research::MPVariable const *'in method 'Constraint_Clear', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_lb', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_ub', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_SetBounds', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_SetBounds', argument 2 of type 'double'in method 'Constraint_SetBounds', argument 3 of type 'double'in method 'Constraint_set_is_lazy', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_set_is_lazy', argument 2 of type 'bool'in method 'Constraint_index', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_dual_value', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_basis_status', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_Lb', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_Ub', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_SetLb', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_SetLb', argument 2 of type 'double'in method 'Constraint_SetUb', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_SetUb', argument 2 of type 'double'in method 'Constraint_DualValue', argument 1 of type 'operations_research::MPConstraint const *'in method 'delete_Objective', argument 1 of type 'operations_research::MPObjective *'in method 'delete_Constraint', argument 1 of type 'operations_research::MPConstraint *'in method 'delete_Variable', argument 1 of type 'operations_research::MPVariable *'in method 'Solver_Solve', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_Solve', argument 2 of type 'operations_research::MPSolverParameters const &'invalid null reference in method 'Solver_Solve', argument 2 of type 'operations_research::MPSolverParameters const &'Wrong number or type of arguments for overloaded function 'Solver_Solve'. Possible C/C++ prototypes are: operations_research::MPSolver::Solve() operations_research::MPSolver::Solve(operations_research::MPSolverParameters const &) in method 'delete_MPSolverParameters', argument 1 of type 'operations_research::MPSolverParameters *'in method 'delete_ModelExportOptions', argument 1 of type 'operations_research::MPModelExportOptions *'in method 'delete_Solver', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_SupportsProblemType', argument 1 of type 'operations_research::MPSolver::OptimizationProblemType'in method 'Solver_LookupVariable', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_LookupVariable', argument 2 of type 'std::string const &'invalid null reference in method 'Solver_LookupVariable', argument 2 of type 'std::string const &'in method 'Solver_Var', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_Var', argument 2 of type 'double'in method 'Solver_Var', argument 3 of type 'double'in method 'Solver_Var', argument 4 of type 'bool'in method 'Solver_Var', argument 5 of type 'std::string const &'invalid null reference in method 'Solver_Var', argument 5 of type 'std::string const &'in method 'Solver_BoolVar', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_BoolVar', argument 2 of type 'std::string const &'invalid null reference in method 'Solver_BoolVar', argument 2 of type 'std::string const &'in method 'Solver_LookupConstraint', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_LookupConstraint', argument 2 of type 'std::string const &'invalid null reference in method 'Solver_LookupConstraint', argument 2 of type 'std::string const &'in method 'Solver_Constraint', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_Constraint', argument 2 of type 'std::string const &'invalid null reference in method 'Solver_Constraint', argument 2 of type 'std::string const &'in method 'Solver_Constraint', argument 2 of type 'double'in method 'Solver_Constraint', argument 3 of type 'double'in method 'Solver_Constraint', argument 4 of type 'std::string const &'invalid null reference in method 'Solver_Constraint', argument 4 of type 'std::string const &'Wrong number or type of arguments for overloaded function 'Solver_Constraint'. Possible C/C++ prototypes are: operations_research::MPSolver::MakeRowConstraint(double,double) operations_research::MPSolver::MakeRowConstraint() operations_research::MPSolver::MakeRowConstraint(double,double,std::string const &) operations_research::MPSolver::MakeRowConstraint(std::string const &) in method 'Solver_Objective', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_CreateSolver', argument 1 of type 'std::string const &'invalid null reference in method 'Solver_CreateSolver', argument 1 of type 'std::string const &'in method 'Variable_SetBranchingPriority', argument 1 of type 'operations_research::MPVariable *'in method 'Variable_SetBranchingPriority', argument 2 of type 'int'MPSolverParameters_GetDoubleParamin method 'MPSolverParameters_GetDoubleParam', argument 1 of type 'operations_research::MPSolverParameters const *'in method 'MPSolverParameters_GetDoubleParam', argument 2 of type 'operations_research::MPSolverParameters::DoubleParam'MPSolverParameters_GetIntegerParamin method 'MPSolverParameters_GetIntegerParam', argument 1 of type 'operations_research::MPSolverParameters const *'in method 'MPSolverParameters_GetIntegerParam', argument 2 of type 'operations_research::MPSolverParameters::IntegerParam'in method 'Solver_SetNumThreads', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_SetNumThreads', argument 2 of type 'int'in method 'Solver_set_time_limit', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_set_time_limit', argument 2 of type 'int64'in method 'Solver_SetTimeLimit', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_SetTimeLimit', argument 2 of type 'int64'MPSolverParameters_SetDoubleParamin method 'MPSolverParameters_SetDoubleParam', argument 1 of type 'operations_research::MPSolverParameters *'in method 'MPSolverParameters_SetDoubleParam', argument 2 of type 'operations_research::MPSolverParameters::DoubleParam'in method 'MPSolverParameters_SetDoubleParam', argument 3 of type 'double'MPSolverParameters_SetIntegerParamin method 'MPSolverParameters_SetIntegerParam', argument 1 of type 'operations_research::MPSolverParameters *'in method 'MPSolverParameters_SetIntegerParam', argument 2 of type 'operations_research::MPSolverParameters::IntegerParam'in method 'MPSolverParameters_SetIntegerParam', argument 3 of type 'int'in method 'Solver_NumVar', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_NumVar', argument 2 of type 'double'in method 'Solver_NumVar', argument 3 of type 'double'in method 'Solver_NumVar', argument 4 of type 'std::string const &'invalid null reference in method 'Solver_NumVar', argument 4 of type 'std::string const &'in method 'Solver_IntVar', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_IntVar', argument 2 of type 'double'in method 'Solver_IntVar', argument 3 of type 'double'in method 'Solver_IntVar', argument 4 of type 'std::string const &'invalid null reference in method 'Solver_IntVar', argument 4 of type 'std::string const &'in method 'Variable_name', argument 1 of type 'operations_research::MPVariable const *'in method 'Constraint_name', argument 1 of type 'operations_research::MPConstraint const *'in method 'Variable___str__', argument 1 of type 'operations_research::MPVariable *'in method 'Variable___repr__', argument 1 of type 'operations_research::MPVariable *'in method 'new_Solver', argument 1 of type 'std::string const &'invalid null reference in method 'new_Solver', argument 1 of type 'std::string const &'in method 'new_Solver', argument 2 of type 'operations_research::MPSolver::OptimizationProblemType'in method 'Solver_constraints', argument 1 of type 'operations_research::MPSolver const *'in method 'Constraint_GetCoefficient', argument 1 of type 'operations_research::MPConstraint const *'in method 'Constraint_SetCoefficient', argument 1 of type 'operations_research::MPConstraint *'in method 'Constraint_SetCoefficient', argument 3 of type 'double'in method 'Objective_GetCoefficient', argument 1 of type 'operations_research::MPObjective const *'in method 'Objective_SetCoefficient', argument 1 of type 'operations_research::MPObjective *'in method 'Objective_SetCoefficient', argument 3 of type 'double'in method 'Solver_variables', argument 1 of type 'operations_research::MPSolver const *'Solver_GLPK_LINEAR_PROGRAMMINGSolver_GLOP_LINEAR_PROGRAMMINGSolver_SCIP_MIXED_INTEGER_PROGRAMMINGSolver_GLPK_MIXED_INTEGER_PROGRAMMINGSolver_CBC_MIXED_INTEGER_PROGRAMMINGSolver_GUROBI_LINEAR_PROGRAMMINGSolver_GUROBI_MIXED_INTEGER_PROGRAMMINGSolver_CPLEX_LINEAR_PROGRAMMINGSolver_CPLEX_MIXED_INTEGER_PROGRAMMINGSolver_XPRESS_LINEAR_PROGRAMMINGSolver_XPRESS_MIXED_INTEGER_PROGRAMMINGSolver_BOP_INTEGER_PROGRAMMINGSolver_SAT_INTEGER_PROGRAMMINGMPSolverParameters_RELATIVE_MIP_GAPMPSolverParameters_PRIMAL_TOLERANCEMPSolverParameters_DUAL_TOLERANCEMPSolverParameters_LP_ALGORITHMMPSolverParameters_INCREMENTALITYMPSolverParameters_PRESOLVE_OFFMPSolverParameters_PRESOLVE_ONMPSolverParameters_INCREMENTALITY_OFFMPSolverParameters_INCREMENTALITY_ONMPSolverParameters_SCALING_OFFFailure to create SWIG globals.in method '__lshift__', argument 1 of type 'std::ostream &'invalid null reference in method '__lshift__', argument 1 of type 'std::ostream &'in method '__lshift__', argument 2 of type 'operations_research::MPSolver::OptimizationProblemType'in method '__lshift__', argument 2 of type 'operations_research::MPSolver::ResultStatus'in method 'Solver_SetHint', argument 1 of type 'operations_research::MPSolver *'sequence(operations_research::MPVariable*) expectedortools/gen/ortools/linear_solver/linear_solver_python_wrap.ccDifferent number of variables and values when setting in method 'Solver_LoadModelFromProto', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_ExportModelToProto', argument 1 of type 'operations_research::MPSolver const *'ortools.linear_solver.linear_solver_pb2in method 'ExportModelAsMpsFormat', argument 2 of type 'operations_research::MPModelExportOptions const &'invalid null reference in method 'ExportModelAsMpsFormat', argument 2 of type 'operations_research::MPModelExportOptions const &'Wrong number or type of arguments for overloaded function 'ExportModelAsMpsFormat'. Possible C/C++ prototypes are: operations_research::ExportModelAsMpsFormatReturnString(operations_research::MPModelProto const &,operations_research::MPModelExportOptions const &) operations_research::ExportModelAsMpsFormatReturnString(operations_research::MPModelProto const &) in method 'ExportModelAsLpFormat', argument 2 of type 'operations_research::MPModelExportOptions const &'invalid null reference in method 'ExportModelAsLpFormat', argument 2 of type 'operations_research::MPModelExportOptions const &'Wrong number or type of arguments for overloaded function 'ExportModelAsLpFormat'. Possible C/C++ prototypes are: operations_research::ExportModelAsLpFormatReturnString(operations_research::MPModelProto const &,operations_research::MPModelExportOptions const &) operations_research::ExportModelAsLpFormatReturnString(operations_research::MPModelProto const &) in method 'Solver_ExportModelAsLpFormat', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_ExportModelAsLpFormat', argument 2 of type 'bool'in method 'Solver_ExportModelAsMpsFormat', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_ExportModelAsMpsFormat', argument 2 of type 'bool'in method 'Solver_ExportModelAsMpsFormat', argument 3 of type 'bool'in method 'Solver_SolveWithProto', argument 1 of type 'operations_research::MPModelRequest const &'invalid null reference in method 'Solver_SolveWithProto', argument 1 of type 'operations_research::MPModelRequest const &'Solver_FillSolutionResponseProtoin method 'Solver_FillSolutionResponseProto', argument 1 of type 'operations_research::MPSolver const *'in method 'Solver_LoadSolutionFromProto', argument 1 of type 'operations_research::MPSolver *'in method 'Solver_LoadSolutionFromProto', argument 3 of type 'double'Wrong number or type of arguments for overloaded function 'Solver_LoadSolutionFromProto'. Possible C/C++ prototypes are: operations_research::MPSolver::LoadSolutionFromProto(operations_research::MPSolutionResponse const &,double) operations_research::MPSolver::LoadSolutionFromProto(operations_research::MPSolutionResponse const &) uint16 *|unsigned short *|uint_least16_t *|uint16_t *uintptr_t *|uint_least64_t *|uint_fast32_t *|uint_fast64_t *|uint64 *|uint64_t *|unsigned long *|uint_fast16_t *|uintmax_t *uint_least32_t *|uint32 *|uint32_t *|unsigned int *unsigned char *|uint8 *|uint_least8_t *|uint_fast8_t *|uint8_t *signed char *|int8 *|int_least8_t *|int_fast8_t *|int8_t *int16 *|short *|int_least16_t *|int16_t *_p_operations_research__MPVariableoperations_research::MPVariable *_p_operations_research__MPSolverParametersoperations_research::MPSolverParameters *_p_operations_research__MPSolveroperations_research::MPSolver *_p_operations_research__MPObjectiveoperations_research::MPObjective *_p_operations_research__MPModelRequestoperations_research::MPModelRequest *_p_operations_research__MPModelExportOptionsoperations_research::MPModelExportOptions *_p_operations_research__MPConstraintoperations_research::MPConstraint *intptr_t *|int_least64_t *|int_fast32_t *|int_fast64_t *|int64 *|int64_t *|long *|int_fast16_t *|intmax_t *int *|int_least32_t *|int32 *|int32_t * Create a solver with the given name and underlying solver backend. Recommended factory method to create a MPSolver instance, especially in non C++ languages. It returns a newly created solver instance if successful, or a nullptr otherwise. This can occur if the relevant interface is not linked in, or if a needed license is not accessible for commercial solvers. Ownership of the solver is passed on to the caller of this method. It will accept both string names of the OptimizationProblemType enum, as well as a short version (i.e. "SCIP_MIXED_INTEGER_PROGRAMMING" or "SCIP"). solver_id is case insensitive, and the following names are supported: - CLP_LINEAR_PROGRAMMING or CLP - CBC_MIXED_INTEGER_PROGRAMMING or CBC - GLOP_LINEAR_PROGRAMMING or GLOP - BOP_INTEGER_PROGRAMMING or BOP - SAT_INTEGER_PROGRAMMING or SAT or CP_SAT - SCIP_MIXED_INTEGER_PROGRAMMING or SCIP - GUROBI_LINEAR_PROGRAMMING or GUROBI_LP - GUROBI_MIXED_INTEGER_PROGRAMMING or GUROBI or GUROBI_MIP - CPLEX_LINEAR_PROGRAMMING or CPLEX_LP - CPLEX_MIXED_INTEGER_PROGRAMMING or CPLEX or CPLEX_MIP - XPRESS_LINEAR_PROGRAMMING or XPRESS_LP - XPRESS_MIXED_INTEGER_PROGRAMMING or XPRESS or XPRESS_MIP - GLPK_LINEAR_PROGRAMMING or GLPK_LP - GLPK_MIXED_INTEGER_PROGRAMMING or GLPK or GLPK_MIP Whether the given problem type is supported (this will depend on the targets that you linked). Clears the objective (including the optimization direction), all variables and constraints. All the other properties of the MPSolver (like the time limit) are kept untouched. Returns the number of variables. Returns the array of variables handled by the MPSolver. (They are listed in the order in which they were created.) Looks up a variable by name, and returns nullptr if it does not exist. The first call has a O(n) complexity, as the variable name index is lazily created upon first use. Will crash if variable names are not unique. Creates a variable with the given bounds, integrality requirement and name. Bounds can be finite or +/- MPSolver::infinity(). The MPSolver owns the variable (i.e. the returned pointer is borrowed). Variable names are optional. If you give an empty name, name() will auto-generate one for you upon request. Creates a continuous variable. Returns the number of constraints. Returns the array of constraints handled by the MPSolver. They are listed in the order in which they were created. Looks up a constraint by name, and returns nullptr if it does not exist. The first call has a O(n) complexity, as the constraint name index is lazily created upon first use. Will crash if constraint names are not unique. *Overload 1:* Creates a linear constraint with given bounds. Bounds can be finite or +/- MPSolver::infinity(). The MPSolver class assumes ownership of the constraint. :rtype: :py:class:`MPConstraint` :return: a pointer to the newly created constraint. | *Overload 2:* Creates a constraint with -infinity and +infinity bounds. | *Overload 3:* Creates a named constraint with given bounds. | *Overload 4:* Creates a named constraint with -infinity and +infinity bounds. Returns the mutable objective object. *Overload 1:* Solves the problem using the default parameter values. | *Overload 2:* Solves the problem using the specified parameter values. Solver_ComputeConstraintActivities Advanced usage: compute the "activities" of all constraints, which are the sums of their linear terms. The activities are returned in the same order as constraints(), which is the order in which constraints were added; but you can also use MPConstraint::index() to get a constraint's index. Advanced usage: Verifies the *correctness* of the solution. It verifies that all variables must be within their domains, all constraints must be satisfied, and the reported objective value must be accurate. Usage: - This can only be called after Solve() was called. - "tolerance" is interpreted as an absolute error threshold. - For the objective value only, if the absolute error is too large, the tolerance is interpreted as a relative error threshold instead. - If "log_errors" is true, every single violation will be logged. - If "tolerance" is negative, it will be set to infinity(). Most users should just set the --verify_solution flag and not bother using this method directly. Interrupts the Solve() execution to terminate processing if possible. If the underlying interface supports interruption; it does that and returns true regardless of whether there's an ongoing Solve() or not. The Solve() call may still linger for a while depending on the conditions. If interruption is not supported; returns false and does nothing. Encodes the current solution in a solution response protocol buffer. Solves the model encoded by a MPModelRequest protocol buffer and fills the solution encoded as a MPSolutionResponse. Note(user): This creates a temporary MPSolver and destroys it at the end. If you want to keep the MPSolver alive (for debugging, or for incremental solving), you should write another version of this function that creates the MPSolver object on the heap and returns it. Note(user): This attempts to first use `DirectlySolveProto()` (if implemented). Consequently, this most likely does *not* override any of the default parameters of the underlying solver. This behavior *differs* from `MPSolver::Solve()` which by default sets the feasibility tolerance and the gap limit (as of 2020/02/11, to 1e-7 and 0.0001, respectively). Exports model to protocol buffer. Advanced usage: pass solver specific parameters in text format. The format is solver-specific and is the same as the corresponding solver configuration file format. Returns true if the operation was successful. Infinity. You can use -MPSolver::infinity() for negative infinity. Returns the number of simplex iterations. Returns the number of branch-and-bound nodes evaluated during the solve. Only available for discrete problems. Solver_ComputeExactConditionNumber Advanced usage: computes the exact condition number of the current scaled basis: L1norm(B) * L1norm(inverse(B)), where B is the scaled basis. This method requires that a basis exists: it should be called after Solve. It is only available for continuous problems. It is implemented for GLPK but not CLP because CLP does not provide the API for doing it. The condition number measures how well the constraint matrix is conditioned and can be used to predict whether numerical issues will arise during the solve: the model is declared infeasible whereas it is feasible (or vice-versa), the solution obtained is not optimal or violates some constraints, the resolution is slow because of repeated singularities. The rule of thumb to interpret the condition number kappa is: - o kappa <= 1e7: virtually no chance of numerical issues - o 1e7 < kappa <= 1e10: small chance of numerical issues - o 1e10 < kappa <= 1e13: medium chance of numerical issues - o kappa > 1e13: high chance of numerical issues The computation of the condition number depends on the quality of the LU decomposition, so it is not very accurate when the matrix is ill conditioned. Some solvers (MIP only, not LP) can produce multiple solutions to the problem. Returns true when another solution is available, and updates the MPVariable* objects to make the new solution queryable. Call only after calling solve. The optimality properties of the additional solutions found, and whether or not the solver computes them ahead of time or when NextSolution() is called is solver specific. As of 2020-02-10, only Gurobi and SCIP support NextSolution(), see linear_solver_interfaces_test for an example of how to configure these solvers for multiple solutions. Other solvers return false unconditionally. Set a hint for solution. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used. A solver that supports this feature will try to use this information to create its initial feasible solution. Note that it may not always be faster to give a hint like this to the solver. There is also no guarantee that the solver will use this hint or try to return a solution "close" to this assignment in case of multiple optimal solutions. Sets the number of threads to be used by the solver. Clears the offset, all variables and coefficients, and the optimization direction. Sets the coefficient of the variable in the objective. If the variable does not belong to the solver, the function just returns, or crashes in non-opt mode. Gets the coefficient of a given variable in the objective It returns 0 if the variable does not appear in the objective). Sets the constant term in the objective. Gets the constant term in the objective. Sets the optimization direction (maximize: true or minimize: false). Sets the optimization direction to minimize. Sets the optimization direction to maximize. Is the optimization direction set to maximize? Is the optimization direction set to minimize? Returns the objective value of the best solution found so far. It is the optimal objective value if the problem has been solved to optimality. Note: the objective value may be slightly different than what you could compute yourself using ``MPVariable::solution_value();`` please use the --verify_solution flag to gain confidence about the numerical stability of your solution. Returns the best objective bound. In case of minimization, it is a lower bound on the objective value of the optimal integer solution. Only available for discrete problems. Returns the name of the variable. Sets the integrality requirement of the variable. Returns the integrality requirement of the variable. Returns the value of the variable in the current solution. If the variable is integer, then the value will always be an integer (the underlying solver handles floating-point values only, but this function automatically rounds it to the nearest integer; see: man 3 round). Returns the index of the variable in the MPSolver::variables_. Sets both the lower and upper bounds. Advanced usage: returns the reduced cost of the variable in the current solution (only available for continuous problems). Advanced usage: returns the basis status of the variable in the current solution (only available for continuous problems). See also: MPSolver::BasisStatus. Advanced usage: Certain MIP solvers (e.g. Gurobi or SCIP) allow you to set a per-variable priority for determining which variable to branch on. A value of 0 is treated as default, and is equivalent to not setting the branching priority. The solver looks first to branch on fractional variables in higher priority levels. As of 2019-05, only Gurobi and SCIP support setting branching priority; all other solvers will simply ignore this annotation. Returns the name of the constraint. Clears all variables and coefficients. Does not clear the bounds. Sets the coefficient of the variable on the constraint. If the variable does not belong to the solver, the function just returns, or crashes in non-opt mode. Gets the coefficient of a given variable on the constraint (which is 0 if the variable does not appear in the constraint). Advanced usage: sets the constraint "laziness". **This is only supported for SCIP and has no effect on other solvers.** When **laziness** is true, the constraint is only considered by the Linear Programming solver if its current solution violates the constraint. In this case, the constraint is definitively added to the problem. This may be useful in some MIP problems, and may have a dramatic impact on performance. For more info see: http://tinyurl.com/lazy-constraints. Returns the index of the constraint in the MPSolver::constraints_. Advanced usage: returns the dual value of the constraint in the current solution (only available for continuous problems). Advanced usage: returns the basis status of the constraint. It is only available for continuous problems). Note that if a constraint "linear_expression in [lb, ub]" is transformed into "linear_expression + slack = 0" with slack in [-ub, -lb], then this status is the same as the status of the slack variable with AT_UPPER_BOUND and AT_LOWER_BOUND swapped. See also: MPSolver::BasisStatus. The constructor sets all parameters to their default value. Sets a double parameter to a specific value. Sets a integer parameter to a specific value. Returns the value of a double parameter. 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