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C++ Reference: lp_utils
Note: This documentation is automatically generated.
Utility functions to interact with an lp solver from the SAT context.
| Function |
Type |
Arguments |
Comments |
ComputeTrueObjectiveLowerBound | Return type: double Arguments: const CpModelProto& model_proto_with_floating_point_objective, const CpObjectiveProto& integer_objective, const int64_t inner_integer_objective_lower_bound |
ConvertBinaryMPModelProtoToBooleanProblem | Return type: bool Arguments: const MPModelProto& mp_model, LinearBooleanProblem* problem |
ConvertBooleanProblemToLinearProgram | Return type: void Arguments: const LinearBooleanProblem& problem, glop::LinearProgram* lp |
ConvertCpModelProtoToMPModelProto | Return type: bool Arguments: const CpModelProto& input, MPModelProto* output |
ConvertMPModelProtoToCpModelProto | Return type: bool Arguments: const SatParameters& params, const MPModelProto& mp_model, CpModelProto* cp_model, SolverLogger* logger |
DetectImpliedIntegers | Return type: std::vector<double> Arguments: MPModelProto* mp_model, SolverLogger* logger |
FindBestScalingAndComputeErrors | Return type: double Arguments: const std::vector<double>& coefficients, const std::vector<double>& lower_bounds, const std::vector<double>& upper_bounds, int64_t max_absolute_activity, double wanted_absolute_activity_precision, double* relative_coeff_error, double* scaled_sum_error |
FindRationalFactor | Return type: int Arguments: double x, int limit = 1e4, double tolerance = 1e-6 |
MakeBoundsOfIntegerVariablesInteger | Return type: bool Arguments: const SatParameters& params, MPModelProto* mp_model, SolverLogger* logger |
MPModelProtoValidationBeforeConversion | Return type: bool Arguments: const SatParameters& params, const MPModelProto& mp_model, SolverLogger* logger |
RemoveNearZeroTerms | Return type: void Arguments: const SatParameters& params, MPModelProto* mp_model, SolverLogger* logger |
ScaleAndSetObjective | Return type: bool Arguments: const SatParameters& params, const std::vector<std::pair<int, double>>& objective, double objective_offset, bool maximize, CpModelProto* cp_model, SolverLogger* logger |
ScaleContinuousVariables | Return type: std::vector<double> Arguments: double scaling, double max_bound, MPModelProto* mp_model |
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Last updated 2024-08-06 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-08-06 UTC."],[[["\u003cp\u003eThe \u003ccode\u003elp_utils\u003c/code\u003e library provides utility functions for interacting with Linear Programming (LP) solvers within the context of the SAT solver.\u003c/p\u003e\n"],["\u003cp\u003eIt includes functions for converting between different problem representations like CpModelProto, MPModelProto, and LinearBooleanProblem.\u003c/p\u003e\n"],["\u003cp\u003eThe library also offers functionalities for scaling variables, manipulating objective functions, and detecting implied integers in the model.\u003c/p\u003e\n"],["\u003cp\u003eThese utilities aim to improve the efficiency and effectiveness of solving optimization problems by leveraging the strengths of both LP and SAT solvers.\u003c/p\u003e\n"]]],["This documentation details utility functions for interacting with LP solvers within a SAT context. Key actions include: converting between `CpModelProto`, `MPModelProto`, and `LinearProgram` formats; computing lower bounds for objectives; validating, scaling, and modifying `MPModelProto` data such as detecting implied integers, adjusting bounds, and removing near-zero terms. Other functionalities include scaling continuous variables, finding rational factors and scaling, and setting objectives in `CpModelProto`. There are also function for converting `BinaryMPModelProto` to `BooleanProblem`\n"],null,["# lp_utils\n\nC++ Reference: lp_utils\n=======================\n\n\nNote: This documentation is automatically generated.\nUtility functions to interact with an lp solver from the SAT context. \n\n| Function | Type | Arguments | Comments |\n|-------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------|----------|\n| [`ComputeTrueObjectiveLowerBound`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L164) | Return type: `double ` Arguments: ` const CpModelProto& model_proto_with_floating_point_objective, const CpObjectiveProto& integer_objective, const int64_t inner_integer_objective_lower_bound` \u003cbr /\u003e |\n| [`ConvertBinaryMPModelProtoToBooleanProblem`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L173) | Return type: `bool ` Arguments: `const MPModelProto& mp_model, LinearBooleanProblem* problem` \u003cbr /\u003e |\n| [`ConvertBooleanProblemToLinearProgram`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L177) | Return type: `void ` Arguments: `const LinearBooleanProblem& problem, glop::LinearProgram* lp` \u003cbr /\u003e |\n| [`ConvertCpModelProtoToMPModelProto`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L136) | Return type: `bool ` Arguments: `const CpModelProto& input, MPModelProto* output` \u003cbr /\u003e |\n| [`ConvertMPModelProtoToCpModelProto`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L124) | Return type: `bool ` Arguments: `const SatParameters& params, const MPModelProto& mp_model, CpModelProto* cp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`DetectImpliedIntegers`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L116) | Return type: `std::vector\u003cdouble\u003e ` Arguments: `MPModelProto* mp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`FindBestScalingAndComputeErrors`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L65) | Return type: `double ` Arguments: ` const std::vector\u003cdouble\u003e& coefficients, const std::vector\u003cdouble\u003e& lower_bounds, const std::vector\u003cdouble\u003e& upper_bounds, int64_t max_absolute_activity, double wanted_absolute_activity_precision, double* relative_coeff_error, double* scaled_sum_error` \u003cbr /\u003e |\n| [`FindRationalFactor`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L43) | Return type: `int ` Arguments: `double x, int limit = 1e4, double tolerance = 1e-6` \u003cbr /\u003e |\n| [`MakeBoundsOfIntegerVariablesInteger`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L91) | Return type: `bool ` Arguments: `const SatParameters& params, MPModelProto* mp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`MPModelProtoValidationBeforeConversion`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L98) | Return type: `bool ` Arguments: `const SatParameters& params, const MPModelProto& mp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`RemoveNearZeroTerms`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L106) | Return type: `void ` Arguments: `const SatParameters& params, MPModelProto* mp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`ScaleAndSetObjective`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L150) | Return type: `bool ` Arguments: `const SatParameters& params, const std::vector\u003cstd::pair\u003cint, double\u003e\u003e& objective, double objective_offset, bool maximize, CpModelProto* cp_model, SolverLogger* logger` \u003cbr /\u003e |\n| [`ScaleContinuousVariables`](https://github.com/google/or-tools/blob/v9.4/ortools/sat/lp_utils.h#L86) | Return type: `std::vector\u003cdouble\u003e ` Arguments: `double scaling, double max_bound, MPModelProto* mp_model` \u003cbr /\u003e |"]]
