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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/* */
/* This file is part of the program and library */
/* SCIP --- Solving Constraint Integer Programs */
/* */
/* Copyright 2002-2022 Zuse Institute Berlin */
/* */
/* Licensed under the Apache License, Version 2.0 (the "License"); */
/* you may not use this file except in compliance with the License. */
/* You may obtain a copy of the License at */
/* */
/* http://www.apache.org/licenses/LICENSE-2.0 */
/* */
/* Unless required by applicable law or agreed to in writing, software */
/* distributed under the License is distributed on an "AS IS" BASIS, */
/* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */
/* See the License for the specific language governing permissions and */
/* limitations under the License. */
/* */
/* You should have received a copy of the Apache-2.0 license */
/* along with SCIP; see the file LICENSE. If not visit scipopt.org. */
/* */
/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/**@file heur_subnlp.h
* @ingroup PRIMALHEURISTICS
* @brief NLP local search primal heuristic using sub-SCIPs
* @author Stefan Vigerske
*
* This heuristic applies a NLP local search to a nonlinear CIP after fixing all discrete variables.
* That is, the CIP is copied, all discrete variables are fixed, presolving is applied,
* and if the resulting CIP has a nonlinear relaxation, then it is tried to solve this relaxation
* by an NLP solver.
* The heuristic only runs if continuous nonlinearities are present (@ref SCIPhasNLPContinuousNonlinearity()).
*
* Fixing values for discrete values are either taken from a solution of the LP relaxation which
* satisfies all integrality constraints, or are provided by SCIPupdateStartpointHeurSubNlp().
*
* This heuristic is orthogonal to the undercover heuristic (@ref heur_undercover.h), which fixes
* variables in a nonlinear CIP in a way that a (possibly mixed-integer) linear subproblem is obtained.
*/
/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
#ifndef HEUR_SUBNLP_H_
#define HEUR_SUBNLP_H_
#include "scip/def.h"
#include "scip/type_heur.h"
#include "scip/type_result.h"
#include "scip/type_retcode.h"
#include "scip/type_scip.h"
#include "scip/type_sol.h"
#include "scip/type_var.h"
#ifdef __cplusplus
extern "C" {
#endif
/** creates the NLP local search primal heuristic and includes it in SCIP
*
* @ingroup PrimalHeuristicIncludes
*/
SCIP_EXPORT
SCIP_RETCODE SCIPincludeHeurSubNlp(
SCIP* scip /**< SCIP data structure */
);
/**@addtogroup PRIMALHEURISTICS
*
* @{
*/
/** main procedure of the subNLP heuristic */
SCIP_EXPORT
SCIP_RETCODE SCIPapplyHeurSubNlp(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< pointer to store result of: solution found, no solution found, or fixing is infeasible (cutoff) */
SCIP_SOL* refpoint, /**< point to take fixation of discrete variables from, and startpoint for NLP solver; if NULL, then LP solution is used */
SCIP_SOL* resultsol /**< a solution where to store found solution values, if any, or NULL if to try adding to SCIP */
);
/** updates the starting point for the NLP heuristic
*
* Is called, for example, by a constraint handler that handles nonlinear constraints when a check on feasibility of a solution fails.
*/
SCIP_EXPORT
SCIP_RETCODE SCIPupdateStartpointHeurSubNlp(
SCIP* scip, /**< SCIP data structure */
SCIP_HEUR* heur, /**< subNLP heuristic */
SCIP_SOL* solcand, /**< solution candidate */
SCIP_Real violation /**< constraint violation of solution candidate */
);
/** gets startpoint candidate to be used in next call to NLP heuristic, or NULL if none */
SCIP_EXPORT
SCIP_SOL* SCIPgetStartCandidateHeurSubNlp(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur /**< heuristic data structure */
);
/** @} */
#ifdef __cplusplus
}
#endif
#endif /*HEUR_SUBNLP_H_*/