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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_proximity.h
* @ingroup PRIMALHEURISTICS
* @brief improvement heuristic which uses an auxiliary objective instead of the original objective function which
* is itself added as a constraint to a sub-SCIP instance. The heuristic was presented by Matteo Fischetti
* and Michele Monaci
* @author Gregor Hendel
*/
/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
#ifndef __SCIP_HEUR_PROXIMITY_H__
#define __SCIP_HEUR_PROXIMITY_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"
#ifdef __cplusplus
extern "C" {
#endif
/** creates the proximity primal heuristic and includes it in SCIP
*
* @ingroup PrimalHeuristicIncludes
*/
SCIP_EXPORT
SCIP_RETCODE SCIPincludeHeurProximity(
SCIP* scip /**< SCIP data structure */
);
/**@addtogroup PRIMALHEURISTICS
*
* @{
*/
/** main procedure of the proximity heuristic, creates and solves a sub-SCIP
*
* @note the method can be applied in an iterative way, keeping the same subscip in between. If the @p freesubscip
* parameter is set to FALSE, the heuristic will keep the subscip data structures. Always set this parameter
* to TRUE, or call SCIPdeleteSubproblemProximity() afterwards
*/
SCIP_EXPORT
SCIP_RETCODE SCIPapplyProximity(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< result data structure */
SCIP_Real minimprove, /**< factor by which proximity should at least improve the incumbent */
SCIP_Longint nnodes, /**< node limit for the subproblem */
SCIP_Longint nlpiters, /**< LP iteration limit for the subproblem */
SCIP_Longint* nusednodes, /**< pointer to store number of used nodes in subscip */
SCIP_Longint* nusedlpiters, /**< pointer to store number of used LP iterations in subscip */
SCIP_Bool freesubscip /**< should the created sub-MIP be freed at the end of the method? */
);
/** frees the sub-MIP created by proximity */
SCIP_EXPORT
SCIP_RETCODE SCIPdeleteSubproblemProximity(
SCIP* scip /** SCIP data structure */
);
/** @} */
#ifdef __cplusplus
}
#endif
#endif