/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/*                                                                           */
/*                  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_undercover.h
 * @ingroup PRIMALHEURISTICS
 * @brief  Undercover primal heuristic for MINLPs
 * @author Timo Berthold
 * @author Ambros Gleixner
 *
 * The undercover heuristic is designed for mixed-integer nonlinear programs and tries to fix a subset of variables such
 * as to make each constraint linear or convex. For this purpose it solves a binary program to automatically determine
 * the minimum number of variable fixings necessary. As fixing values, we use values from the LP relaxation, the NLP
 * relaxation, or the incumbent solution.
 */

/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/

#ifndef __SCIP_HEUR_UNDERCOVER_H__
#define __SCIP_HEUR_UNDERCOVER_H__

#include "scip/def.h"
#include "scip/type_retcode.h"
#include "scip/type_scip.h"
#include "scip/type_var.h"

#ifdef __cplusplus
extern "C" {
#endif

/** creates the undercover primal heuristic and includes it in SCIP
 *
 *  @ingroup PrimalHeuristicIncludes
 */
SCIP_EXPORT
SCIP_RETCODE SCIPincludeHeurUndercover(
   SCIP*                 scip                /**< SCIP data structure */
   );

/**@addtogroup PRIMALHEURISTICS
 *
 * @{
 */

/** computes a minimal set of covering variables */
SCIP_EXPORT
SCIP_RETCODE SCIPcomputeCoverUndercover(
   SCIP*                 scip,               /**< SCIP data structure */
   int*                  coversize,          /**< size of the computed cover */
   SCIP_VAR**            cover,              /**< pointer to store the variables (of the original SCIP) in the computed cover
                                              *   (should be ready to hold SCIPgetNVars(scip) entries) */
   SCIP_Real             timelimit,          /**< time limit */
   SCIP_Real             memorylimit,        /**< memory limit */
   SCIP_Real             objlimit,           /**< objective limit: upper bound on coversize */
   SCIP_Bool             globalbounds,       /**< should global bounds on variables be used instead of local bounds at focus node? */
   SCIP_Bool             onlyconvexify,      /**< should we only fix/dom.red. variables creating nonconvexity? */
   SCIP_Bool             coverbd,            /**< should bounddisjunction constraints be covered (or just copied)? */
   char                  coveringobj,        /**< objective function of the covering problem ('b'ranching status,
                                              *   influenced nonlinear 'c'onstraints/'t'erms, 'd'omain size, 'l'ocks,
                                              *   'm'in of up/down locks, 'u'nit penalties, constraint 'v'iolation) */
   SCIP_Bool*            success             /**< feasible cover found? */
   );

/** @} */

#ifdef __cplusplus
}
#endif

#endif