1 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ 2 /* */ 3 /* This file is part of the program and library */ 4 /* SCIP --- Solving Constraint Integer Programs */ 5 /* */ 6 /* Copyright (C) 2002-2021 Konrad-Zuse-Zentrum */ 7 /* fuer Informationstechnik Berlin */ 8 /* */ 9 /* SCIP is distributed under the terms of the ZIB Academic License. */ 10 /* */ 11 /* You should have received a copy of the ZIB Academic License */ 12 /* along with SCIP; see the file COPYING. If not visit scipopt.org. */ 13 /* */ 14 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ 15 16 /**@file heuristics.h 17 * @ingroup PUBLICCOREAPI 18 * @brief methods commonly used by primal heuristics 19 * @author Gregor Hendel 20 */ 21 22 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/ 23 24 #ifndef __SCIP_HEURISTICS_H__ 25 #define __SCIP_HEURISTICS_H__ 26 27 #include "scip/def.h" 28 #include "scip/type_scip.h" 29 #include "scip/type_heur.h" 30 #include "scip/type_misc.h" 31 #include "scip/type_retcode.h" 32 #include "scip/type_sol.h" 33 #include "scip/type_var.h" 34 35 #ifdef __cplusplus 36 extern "C" { 37 #endif 38 39 /**@defgroup PublicSpecialHeuristicMethods Special Methods 40 * @ingroup PublicHeuristicMethods 41 * @brief methods commonly used by primal heuristics 42 * 43 * @{ 44 */ 45 46 /** performs a diving within the limits of the @p diveset parameters 47 * 48 * This method performs a diving according to the settings defined by the diving settings @p diveset; Contrary to the 49 * name, SCIP enters probing mode (not diving mode) and dives along a path into the tree. Domain propagation 50 * is applied at every node in the tree, whereas probing LPs might be solved less frequently. 51 * 52 * Starting from the current LP solution, the algorithm selects candidates which maximize the 53 * score defined by the @p diveset and whose solution value has not yet been rendered infeasible by propagation, 54 * and propagates the bound change on this candidate. 55 * 56 * The algorithm iteratively selects the the next (unfixed) candidate in the list, until either enough domain changes 57 * or the resolve frequency of the LP trigger an LP resolve (and hence, the set of potential candidates changes), 58 * or the last node is proven to be infeasible. It optionally backtracks and tries the 59 * other branching direction. 60 * 61 * After the set of remaining candidates is empty or the targeted depth is reached, the node LP is 62 * solved, and the old candidates are replaced by the new LP candidates. 63 * 64 * @see heur_guideddiving.c for an example implementation of a dive set controlling the diving algorithm. 65 * 66 * @note the node from where the algorithm is called is checked for a basic LP solution. If the solution 67 * is non-basic, e.g., when barrier without crossover is used, the method returns without performing a dive. 68 * 69 * @note currently, when multiple diving heuristics call this method and solve an LP at the same node, only the first 70 * call will be executed, @see SCIPgetLastDiveNode(). 71 */ 72 SCIP_EXPORT 73 SCIP_RETCODE SCIPperformGenericDivingAlgorithm( 74 SCIP* scip, /**< SCIP data structure */ 75 SCIP_DIVESET* diveset, /**< settings for diving */ 76 SCIP_SOL* worksol, /**< non-NULL working solution */ 77 SCIP_HEUR* heur, /**< the calling primal heuristic */ 78 SCIP_RESULT* result, /**< SCIP result pointer */ 79 SCIP_Bool nodeinfeasible, /**< is the current node known to be infeasible? */ 80 SCIP_Longint iterlim, /**< nonnegative iteration limit for the LP solves, or -1 for dynamic setting */ 81 SCIP_DIVECONTEXT divecontext /**< context for diving statistics */ 82 ); 83 84 /** get a sub-SCIP copy of the transformed problem */ 85 SCIP_EXPORT 86 SCIP_RETCODE SCIPcopyLargeNeighborhoodSearch( 87 SCIP* sourcescip, /**< source SCIP data structure */ 88 SCIP* subscip, /**< sub-SCIP used by the heuristic */ 89 SCIP_HASHMAP* varmap, /**< a hashmap to store the mapping of source variables to the corresponding 90 * target variables */ 91 const char* suffix, /**< suffix for the problem name */ 92 SCIP_VAR** fixedvars, /**< source variables whose copies should be fixed in the target SCIP environment, or NULL */ 93 SCIP_Real* fixedvals, /**< array of fixing values for target SCIP variables, or NULL */ 94 int nfixedvars, /**< number of source variables whose copies should be fixed in the target SCIP environment, or NULL */ 95 SCIP_Bool uselprows, /**< should the linear relaxation of the problem defined by LP rows be copied? */ 96 SCIP_Bool copycuts, /**< should cuts be copied (only if uselprows == FALSE) */ 97 SCIP_Bool* success, /**< was the copying successful? */ 98 SCIP_Bool* valid /**< pointer to store whether the copying was valid, or NULL */ 99 ); 100 101 /** adds a trust region neighborhood constraint to the @p targetscip 102 * 103 * a trust region constraint measures the deviation from the current incumbent solution \f$x^*\f$ by an auxiliary 104 * continuous variable \f$v \geq 0\f$: 105 * \f[ 106 * \sum\limits_{j\in B} |x_j^* - x_j| = v 107 * \f] 108 * Only binary variables are taken into account. The deviation is penalized in the objective function using 109 * a positive \p violpenalty. 110 * 111 * @note: the trust region constraint creates an auxiliary variable to penalize the deviation from 112 * the current incumbent solution. This variable can afterwards be accessed using SCIPfindVar() by its name 113 * 'trustregion_violationvar' 114 */ 115 SCIP_EXPORT 116 SCIP_RETCODE SCIPaddTrustregionNeighborhoodConstraint( 117 SCIP* scip, /**< the SCIP data structure */ 118 SCIP* subscip, /**< SCIP data structure of the subproblem */ 119 SCIP_VAR** subvars, /**< variables of the subproblem, NULL entries are ignored */ 120 SCIP_Real violpenalty /**< the penalty for violating the trust region */ 121 ); 122 123 /** @} */ 124 125 #ifdef __cplusplus 126 } 127 #endif 128 129 #endif 130