1 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ 2 /* */ 3 /* This file is part of the program and library */ 4 /* SCIP --- Solving Constraint Integer Programs */ 5 /* */ 6 /* Copyright (c) 2002-2023 Zuse Institute Berlin (ZIB) */ 7 /* */ 8 /* Licensed under the Apache License, Version 2.0 (the "License"); */ 9 /* you may not use this file except in compliance with the License. */ 10 /* You may obtain a copy of the License at */ 11 /* */ 12 /* http://www.apache.org/licenses/LICENSE-2.0 */ 13 /* */ 14 /* Unless required by applicable law or agreed to in writing, software */ 15 /* distributed under the License is distributed on an "AS IS" BASIS, */ 16 /* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */ 17 /* See the License for the specific language governing permissions and */ 18 /* limitations under the License. */ 19 /* */ 20 /* You should have received a copy of the Apache-2.0 license */ 21 /* along with SCIP; see the file LICENSE. If not visit scipopt.org. */ 22 /* */ 23 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ 24 25 /**@file heur_dps.h 26 * @ingroup PRIMALHEURISTICS 27 * @brief dynamic partition search 28 * @author Katrin Halbig 29 * 30 * The dynamic partition search (DPS) is a construction heuristic which additionally needs a 31 * user decomposition with linking constraints only. 32 * 33 * This heuristic splits the problem into several sub-SCIPs according to the given decomposition. Thereby the linking constraints 34 * with their right-hand and left-hand sides are also split. DPS searches for a partition of the sides on the blocks 35 * so that a feasible solution is obtained. 36 * For each block the parts of the original linking constraints are extended by slack variables. Moreover, the objective function 37 * is replaced by the sum of these additional variables weighted by penalty parameters lambda. If all blocks have an optimal solution 38 * of zero, the algorithm terminates with a feasible solution for the main problem. Otherwise, the partition and the penalty parameters 39 * are updated, and the sub-SCIPs are solved again. 40 * 41 * A detailed description can be found in 42 * K. Halbig, A. Göß and D. Weninger (2023). Exploiting user-supplied Decompositions inside Heuristics. https://optimization-online.org/?p=23386 43 */ 44 45 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/ 46 47 #ifndef __SCIP_HEUR_DPS_H__ 48 #define __SCIP_HEUR_DPS_H__ 49 50 51 #include "scip/def.h" 52 #include "scip/type_retcode.h" 53 #include "scip/type_scip.h" 54 55 #ifdef __cplusplus 56 extern "C" { 57 #endif 58 59 /** creates the dps primal heuristic and includes it in SCIP 60 * 61 * @ingroup PrimalHeuristicIncludes 62 */ 63 SCIP_EXPORT 64 SCIP_RETCODE SCIPincludeHeurDps( 65 SCIP* scip /**< SCIP data structure */ 66 ); 67 68 #ifdef __cplusplus 69 } 70 #endif 71 72 #endif 73