/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ /* */ /* 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