NLP local search primal heuristic using sub-SCIPs.
This heuristic applies a NLP local search to a nonlinear CIP after fixing all discrete variables. That is, the CIP is copied, all discrete variables are fixed, presolving is applied, and if the resulting CIP has a nonlinear relaxation, then it is tried to solve this relaxation by an NLP solver. The heuristic only runs if continuous nonlinearities are present (SCIPhasNLPContinuousNonlinearity()).
Fixing values for discrete values are either taken from a solution of the LP relaxation which satisfies all integrality constraints, or are provided by SCIPupdateStartpointHeurSubNlp().
This heuristic is orthogonal to the undercover heuristic (heur_undercover.h), which fixes variables in a nonlinear CIP in a way that a (possibly mixed-integer) linear subproblem is obtained.
Definition in file heur_subnlp.h.
Go to the source code of this file.
|SCIP_RETCODE||SCIPincludeHeurSubNlp (SCIP *scip)|
|SCIP_RETCODE||SCIPapplyHeurSubNlp (SCIP *scip, SCIP_HEUR *heur, SCIP_RESULT *result, SCIP_SOL *refpoint, SCIP_SOL *resultsol)|
|SCIP_RETCODE||SCIPupdateStartpointHeurSubNlp (SCIP *scip, SCIP_HEUR *heur, SCIP_SOL *solcand, SCIP_Real violation)|
|SCIP_SOL *||SCIPgetStartCandidateHeurSubNlp (SCIP *scip, SCIP_HEUR *heur)|