heur_gins.h
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18 * @brief LNS heuristic that tries to delimit the search region to a neighborhood in the constraint graph
22 * Graph Induced Neighborhood Search (GINS) is a Large Neighborhood Search Heuristic that attempts to improve
23 * an incumbent solution by fixing a suitable percentage of integer variables to the incumbent and
26 * Its search neighborhoods are based on distances in a bipartite graph \f$G\f$ with the variables and constraints as nodes and
28 * Given an integer \f$k\f$, the \f$k\f$-neighborhood of a variable \f$v\f$ in \f$G\f$ is the set of variables, whose nodes
29 * are connected to \f$v\f$ by a path not longer than \f$2 \cdot k\f$. Intuitively, a judiciously chosen neighborhood size
32 * An initial variable selection is made by randomly sampling different neighborhoods across the whole main problem.
33 * The neighborhood that offers the largest potential for improvement is selected to become the local search neighborhood,
36 * GINS also supports a rolling horizon approach, during which several local neighborhoods are considered
37 * with increasing distance to the variable selected for the initial sub-problem. The rolling horizon approach ends
38 * if no improvement could be found or a sufficient part of the problem component variables has been part of
42 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
Definition: struct_scip.h:59
type definitions for return codes for SCIP methods
type definitions for SCIP's main datastructure
SCIP_EXPORT SCIP_RETCODE SCIPincludeHeurGins(SCIP *scip)
Definition: heur_gins.c:2690
common defines and data types used in all packages of SCIP
Definition: objbenders.h:33