/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ /* */ /* This file is part of the program and library */ /* SCIP --- Solving Constraint Integer Programs */ /* */ /* Copyright (C) 2002-2020 Konrad-Zuse-Zentrum */ /* fuer Informationstechnik Berlin */ /* */ /* SCIP is distributed under the terms of the ZIB Academic License. */ /* */ /* You should have received a copy of the ZIB Academic License */ /* along with SCIP; see the file COPYING. If not visit scipopt.org. */ /* */ /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */ /**@file sepa_gauge.h * @ingroup SEPARATORS * @brief gauge separator * @author Felipe Serrano * * This separator receives a point \f$ x_0 \f$ to separate and, given an interior point \f$ \bar x \f$, finds the * intersection between the boundary of a convex relaxation of the current problem and the segment joining \f$ x_0 \f$ * and \f$ \bar x \f$. Then it generates gradient cuts at the intersection. * * The interior point \f$ \bar x \f$ is computed only once, by solving * \f[ * \min t \\ * \f] * \f[ * s.t. \; g_j(x) \le t \, \forall j=1,\ldots,m * \f] * \f[ * l_k(x) \le 0 \, \forall k=1,\ldots,p * \f] * where each \f$ g_j \f$ is a convex function and \f$ l_k \f$ is a linear function and * \f[ * C = \{ x \colon g_j(x) \le 0 \, \forall j=1,\ldots,m, l_k(x) \le 0 \, \forall k=1,\ldots,p \} * \f] * is a convex relaxation of the current problem. * If we can not find an interior solution, the separator will not be executed again. * * Note that we do not try to push the linear constraints into the interior, i.e. we use \f$ l_k(x) \le 0 \f$ instead * of \f$ l_k(x) \le t \f$, since some of the inequalities might actually be equalities, forcing \f$ t \f$ to zero. * We also use an arbitrary lower bound on \f$ t \f$ to handle the case when \f$ C \f$ is unbounded. * * By default, the separator runs only if the convex relaxation has at least two nonlinear convex constraints. * * In order to compute the boundary point, we consider only nonlinear convex constraints that are violated by the point * we want to separate. These constraints define a convex region for which \f$ \bar x \f$ is an interior point. Then, * a binary search is perform on the segment \f$[\bar x, x_0]\f$ in order to find the boundary point. Gradient cuts are * computed for each of these nonlinear convex constraints which are active at the boundary point. * * Technical details: * - We consider a constraint for the binary search, only when its violation is larger than \f$ 10^{-4} \f$, see * MIN_VIOLATION in sepa_gauge.c. The reason is that if the violation is too small, chances are that the point in the * boundary is in the interior for this constraint and we wouldn't generate a cut for it anyway. On the other hand, * even if we generate a cut for this constraint, it is likely that the boundary point is very close to the point to * separate. Hence the cut generate would be very similar to the gradient cut at the point to separate. * - Before separating, if a slight perturbation of the interior point in the direction of the point to separate is * gives a point outside the region, we do not separate. The reason is that the interior point we computed could be * almost at the boundary and the segment \f$[\bar x, x_0]\f$ could be tangent to the region. In that case, the cuts * we generate will not separate \f$ x_0 \f$ from the feasible region. */ /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/ #ifndef __SCIP_SEPA_GAUGE_H__ #define __SCIP_SEPA_GAUGE_H__ #include "scip/def.h" #include "scip/type_retcode.h" #include "scip/type_scip.h" #ifdef __cplusplus extern "C" { #endif /** creates the gauge separator and includes it in SCIP * * @ingroup SeparatorIncludes */ SCIP_EXPORT SCIP_RETCODE SCIPincludeSepaGauge( SCIP* scip /**< SCIP data structure */ ); #ifdef __cplusplus } #endif #endif