Example #1
0
/** main procedure of the zeroobj heuristic, creates and solves a sub-SCIP */
SCIP_RETCODE SCIPapplyZeroobj(
   SCIP*                 scip,               /**< original SCIP data structure                                        */
   SCIP_HEUR*            heur,               /**< heuristic data structure                                            */
   SCIP_RESULT*          result,             /**< result data structure                                               */
   SCIP_Real             minimprove,         /**< factor by which zeroobj should at least improve the incumbent      */
   SCIP_Longint          nnodes              /**< node limit for the subproblem                                       */
   )
{
   SCIP*                 subscip;            /* the subproblem created by zeroobj              */
   SCIP_HASHMAP*         varmapfw;           /* mapping of SCIP variables to sub-SCIP variables */
   SCIP_VAR**            vars;               /* original problem's variables                    */
   SCIP_VAR**            subvars;            /* subproblem's variables                          */
   SCIP_HEURDATA*        heurdata;           /* heuristic's private data structure              */
   SCIP_EVENTHDLR*       eventhdlr;          /* event handler for LP events                     */

   SCIP_Real cutoff;                         /* objective cutoff for the subproblem             */
   SCIP_Real timelimit;                      /* time limit for zeroobj subproblem              */
   SCIP_Real memorylimit;                    /* memory limit for zeroobj subproblem            */
   SCIP_Real large;

   int nvars;                                /* number of original problem's variables          */
   int i;

   SCIP_Bool success;
   SCIP_Bool valid;
   SCIP_RETCODE retcode;
   SCIP_SOL** subsols;
   int nsubsols;

   assert(scip != NULL);
   assert(heur != NULL);
   assert(result != NULL);

   assert(nnodes >= 0);
   assert(0.0 <= minimprove && minimprove <= 1.0);

   *result = SCIP_DIDNOTRUN;

   /* only call heuristic once at the root */
   if( SCIPgetDepth(scip) <= 0 && SCIPheurGetNCalls(heur) > 0 )
      return SCIP_OKAY;

   /* get heuristic data */
   heurdata = SCIPheurGetData(heur);
   assert(heurdata != NULL);

   /* only call the heuristic if we do not have an incumbent  */
   if( SCIPgetNSolsFound(scip) > 0 && heurdata->onlywithoutsol )
      return SCIP_OKAY;

   /* check whether there is enough time and memory left */
   timelimit = 0.0;
   memorylimit = 0.0;
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   /* get variable data */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initialize the subproblem */
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );

   /* different methods to create sub-problem: either copy LP relaxation or the CIP with all constraints */
   valid = FALSE;

   /* copy complete SCIP instance */
   SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "zeroobj", TRUE, FALSE, TRUE, &valid) );
   SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");

   /* create event handler for LP events */
   eventhdlr = NULL;
   SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecZeroobj, NULL) );
   if( eventhdlr == NULL )
   {
      SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
      return SCIP_PLUGINNOTFOUND;
   }

   /* determine large value to set variables to */
   large = SCIPinfinity(scip);
   if( !SCIPisInfinity(scip, 0.1 / SCIPfeastol(scip)) )
      large = 0.1 / SCIPfeastol(scip);

   /* get variable image and change to 0.0 in sub-SCIP */
   for( i = 0; i < nvars; i++ )
   {
      SCIP_Real adjustedbound;
      SCIP_Real lb;
      SCIP_Real ub;
      SCIP_Real inf;
      
      subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
      SCIP_CALL( SCIPchgVarObj(subscip, subvars[i], 0.0) );

      lb = SCIPvarGetLbGlobal(subvars[i]);
      ub = SCIPvarGetUbGlobal(subvars[i]);
      inf = SCIPinfinity(subscip);

      /* adjust infinite bounds in order to avoid that variables with non-zero objective 
       * get fixed to infinite value in zeroobj subproblem
       */
      if( SCIPisInfinity(subscip, ub ) )
      {
         adjustedbound = MAX(large, lb+large);
         adjustedbound = MIN(adjustedbound, inf);
         SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], adjustedbound) );
      }
      if( SCIPisInfinity(subscip, -lb ) )
      {
         adjustedbound = MIN(-large, ub-large);
         adjustedbound = MAX(adjustedbound, -inf);
         SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], adjustedbound) );
      }
   }

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
   SCIP_CALL( SCIPsetIntParam(subscip, "limits/solutions", 1) );

   /* forbid recursive call of heuristics and separators solving sub-SCIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable expensive techniques that merely work on the dual bound */

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
   if( !SCIPisParamFixed(subscip, "presolving/maxrounds") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "presolving/maxrounds", 50) );
   }

   /* use best dfs node selection */
   if( SCIPfindNodesel(subscip, "dfs") != NULL && !SCIPisParamFixed(subscip, "nodeselection/dfs/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/leastinf/priority", INT_MAX/4) );
   }

   /* employ a limit on the number of enforcement rounds in the quadratic constraint handler; this fixes the issue that
    * sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
    * feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
    * instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no deductions shall be
    * made for the original SCIP
    */
   if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 10) );
   }

   /* disable feaspump and fracdiving */
   if( !SCIPisParamFixed(subscip, "heuristics/feaspump/freq") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/feaspump/freq", -1) );
   }
   if( !SCIPisParamFixed(subscip, "heuristics/fracdiving/freq") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/fracdiving/freq", -1) );
   }

   /* restrict LP iterations */
   SCIP_CALL( SCIPsetLongintParam(subscip, "lp/iterlim", 2*heurdata->maxlpiters / MAX(1,nnodes)) );
   SCIP_CALL( SCIPsetLongintParam(subscip, "lp/rootiterlim", heurdata->maxlpiters) );

#ifdef SCIP_DEBUG
   /* for debugging zeroobj, enable MIP output */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
   SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif

   /* if there is already a solution, add an objective cutoff */
   if( SCIPgetNSols(scip) > 0 )
   {
      SCIP_Real upperbound;
      SCIP_CONS* origobjcons;
#ifndef NDEBUG
      int nobjvars;
      nobjvars = 0;
#endif

      cutoff = SCIPinfinity(scip);
      assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );

      upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);

      if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
      {
         cutoff = (1-minimprove)*SCIPgetUpperbound(scip) + minimprove*SCIPgetLowerbound(scip);
      }
      else
      {
         if( SCIPgetUpperbound(scip) >= 0 )
            cutoff = ( 1 - minimprove ) * SCIPgetUpperbound ( scip );
         else
            cutoff = ( 1 + minimprove ) * SCIPgetUpperbound ( scip );
      }
      cutoff = MIN(upperbound, cutoff);

      SCIP_CALL( SCIPcreateConsLinear(subscip, &origobjcons, "objbound_of_origscip", 0, NULL, NULL, -SCIPinfinity(subscip), cutoff,
            TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
      for( i = 0; i < nvars; ++i)
      {
         if( !SCIPisFeasZero(subscip, SCIPvarGetObj(vars[i])) )
         {
            SCIP_CALL( SCIPaddCoefLinear(subscip, origobjcons, subvars[i], SCIPvarGetObj(vars[i])) );
#ifndef NDEBUG
            nobjvars++;
#endif
         }
      }
      SCIP_CALL( SCIPaddCons(subscip, origobjcons) );
      SCIP_CALL( SCIPreleaseCons(subscip, &origobjcons) );
      assert(nobjvars == SCIPgetNObjVars(scip));
   }

   /* catch LP events of sub-SCIP */
   SCIP_CALL( SCIPtransformProb(subscip) );
   SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );

   SCIPdebugMessage("solving subproblem: nnodes=%"SCIP_LONGINT_FORMAT"\n", nnodes);
   retcode = SCIPsolve(subscip);

   /* drop LP events of sub-SCIP */
   SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );

   /* errors in solving the subproblem should not kill the overall solving process;
    * hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   /* check, whether a solution was found;
    * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
    */
   nsubsols = SCIPgetNSols(subscip);
   subsols = SCIPgetSols(subscip);
   success = FALSE;
   for( i = 0; i < nsubsols && (!success || heurdata->addallsols); ++i )
   {
      SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      if( success )
         *result = SCIP_FOUNDSOL;
   }

#ifdef SCIP_DEBUG
   SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif

   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Example #2
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMutation)
{  /*lint --e{715}*/
   SCIP_Longint maxnnodes;
   SCIP_Longint nsubnodes;                   /* node limit for the subproblem                       */

   SCIP_HEURDATA* heurdata;                  /* heuristic's data                                    */
   SCIP* subscip;                            /* the subproblem created by mutation                  */
   SCIP_VAR** vars;                          /* original problem's variables                        */
   SCIP_VAR** subvars;                       /* subproblem's variables                              */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */

   SCIP_Real cutoff;                         /* objective cutoff for the subproblem                 */
   SCIP_Real maxnnodesr;
   SCIP_Real memorylimit;
   SCIP_Real timelimit;                      /* timelimit for the subproblem                        */
   SCIP_Real upperbound;

   int nvars;                                /* number of original problem's variables              */
   int i;

   SCIP_Bool success;

   SCIP_RETCODE retcode;

   assert( heur != NULL );
   assert( scip != NULL );
   assert( result != NULL );

   /* get heuristic's data */
   heurdata = SCIPheurGetData(heur);
   assert( heurdata != NULL );

   *result = SCIP_DELAYED;

   /* only call heuristic, if feasible solution is available */
   if( SCIPgetNSols(scip) <= 0 )
      return SCIP_OKAY;

   /* only call heuristic, if the best solution comes from transformed problem */
   assert( SCIPgetBestSol(scip) != NULL );
   if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
      return SCIP_OKAY;

   /* only call heuristic, if enough nodes were processed since last incumbent */
   if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip))  < heurdata->nwaitingnodes)
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* only call heuristic, if discrete variables are present */
   if( SCIPgetNBinVars(scip) == 0 && SCIPgetNIntVars(scip) == 0 )
      return SCIP_OKAY;

   /* calculate the maximal number of branching nodes until heuristic is aborted */
   maxnnodesr = heurdata->nodesquot * SCIPgetNNodes(scip);

   /* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
   maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
   maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
   maxnnodes += heurdata->nodesofs;

   /* determine the node limit for the current process */
   nsubnodes = maxnnodes - heurdata->usednodes;
   nsubnodes = MIN(nsubnodes, heurdata->maxnodes);

   /* check whether we have enough nodes left to call subproblem solving */
   if( nsubnodes < heurdata->minnodes )
       return SCIP_OKAY;

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initializing the subproblem */
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );

   if( heurdata->uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_mutationsub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_mutationsub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_Bool valid;
      valid = FALSE;

      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rens", TRUE, FALSE, TRUE, &valid) );

      if( heurdata->copycuts )
      {
         /* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }

      SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
   }

   for( i = 0; i < nvars; i++ )
     subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
   SCIP_CALL( createSubproblem(scip, subscip, subvars, heurdata->minfixingrate, &heurdata->randseed, heurdata->uselprows) );

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

  /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   if( !SCIPisParamFixed(subscip, "conflict/useprop") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usesb") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
   }

   /* employ a limit on the number of enforcement rounds in the quadratic constraint handlers; this fixes the issue that
    * sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
    * feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
    * instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no decutions shall be
    * made for the original SCIP
    */
   if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 10) );
   }

   /* add an objective cutoff */
   cutoff = SCIPinfinity(scip);
   assert( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) );

   upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
   if( !SCIPisInfinity(scip, -1.0 * SCIPgetLowerbound(scip)) )
   {
      cutoff = (1-heurdata->minimprove) * SCIPgetUpperbound(scip) + heurdata->minimprove * SCIPgetLowerbound(scip);
   }
   else
   {
      if( SCIPgetUpperbound ( scip ) >= 0 )
         cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
      else
         cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
   }
   cutoff = MIN(upperbound, cutoff );
   SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );

   /* solve the subproblem */
   SCIPdebugMessage("Solve Mutation subMIP\n");
   retcode = SCIPsolve(subscip);

   /* Errors in solving the subproblem should not kill the overall solving process
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in Mutation heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   heurdata->usednodes += SCIPgetNNodes(subscip);

   /* check, whether a solution was found */
   if( SCIPgetNSols(subscip) > 0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      }
      if( success )
         *result = SCIP_FOUNDSOL;
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Example #3
0
/** main procedure of the RENS heuristic, creates and solves a subMIP */
SCIP_RETCODE SCIPapplyGcgrens(
   SCIP*                 scip,               /**< original SCIP data structure                                   */
   SCIP_HEUR*            heur,               /**< heuristic data structure                                       */
   SCIP_RESULT*          result,             /**< result data structure                                          */
   SCIP_Real             minfixingrate,      /**< minimum percentage of integer variables that have to be fixed  */
   SCIP_Real             minimprove,         /**< factor by which RENS should at least improve the incumbent     */
   SCIP_Longint          maxnodes,           /**< maximum number of  nodes for the subproblem                    */
   SCIP_Longint          nstallnodes,        /**< number of stalling nodes for the subproblem                    */
   SCIP_Bool             binarybounds,       /**< should general integers get binary bounds [floor(.),ceil(.)]?  */
   SCIP_Bool             uselprows           /**< should subproblem be created out of the rows in the LP rows?   */
   )
{
   SCIP* subscip;                            /* the subproblem created by RENS                  */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */
   SCIP_VAR** vars;                          /* original problem's variables                    */
   SCIP_VAR** subvars;                       /* subproblem's variables                          */

   SCIP_Real cutoff;                         /* objective cutoff for the subproblem             */
   SCIP_Real timelimit;
   SCIP_Real memorylimit;

   int nvars;
   int i;

   SCIP_Bool success;
   SCIP_RETCODE retcode;

   assert(scip != NULL);
   assert(heur != NULL);
   assert(result != NULL);

   assert(maxnodes >= 0);
   assert(nstallnodes >= 0);

   assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
   assert(0.0 <= minimprove && minimprove <= 1.0);

   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initialize the subproblem */
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );

   if( uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_gcgrenssub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_gcgrenssub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_Bool valid;
      SCIP_HEURDATA* heurdata;

      valid = FALSE;

      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "gcgrens", TRUE, FALSE, TRUE, &valid) ); /** @todo check for thread safeness */

      /* get heuristic's data */
      heurdata = SCIPheurGetData(heur);
      assert( heurdata != NULL );

      if( heurdata->copycuts )
      {
         /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }

      SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
   }

   for( i = 0; i < nvars; i++ )
     subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
   SCIP_CALL( createSubproblem(scip, subscip, subvars, minfixingrate, binarybounds, uselprows, &success) );
   SCIPdebugMessage("RENS subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

   /* check whether there is enough time and memory left */
   timelimit = 0.0;
   memorylimit = 0.0;
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
   if( !SCIPisInfinity(scip, memorylimit) )
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
   if( timelimit <= 0.0 || memorylimit <= 0.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", nstallnodes) );
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", maxnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving sub-SCIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(scip, "estimate") != NULL )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(scip, "inference") != NULL )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );


#ifdef SCIP_DEBUG
   /* for debugging RENS, enable MIP output */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
   SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif


   /* if the subproblem could not be created, free memory and return */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;
      SCIPfreeBufferArray(scip, &subvars);
      SCIP_CALL( SCIPfree(&subscip) );
      return SCIP_OKAY;
   }

   /* if there is already a solution, add an objective cutoff */
   if( SCIPgetNSols(scip) > 0 )
   {
      SCIP_Real upperbound;
      assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );

      upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);

      if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
      {
         cutoff = (1-minimprove)*SCIPgetUpperbound(scip) + minimprove*SCIPgetLowerbound(scip);
      }
      else
      {
         if( SCIPgetUpperbound ( scip ) >= 0 )
            cutoff = ( 1 - minimprove ) * SCIPgetUpperbound ( scip );
         else
            cutoff = ( 1 + minimprove ) * SCIPgetUpperbound ( scip );
      }
      cutoff = MIN(upperbound, cutoff);
      SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
   }

   /* presolve the subproblem */
   retcode = SCIPpresolve(subscip);

   /* Errors in solving the subproblem should not kill the overall solving process
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while presolving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   SCIPdebugMessage("GCG RENS presolved subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);

   /* after presolving, we should have at least reached a certain fixing rate over ALL variables (including continuous)
    * to ensure that not only the MIP but also the LP relaxation is easy enough
    */
   if( ( nvars - SCIPgetNVars(subscip) ) / (SCIP_Real)nvars >= minfixingrate / 2.0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;

      /* solve the subproblem */
      SCIPdebugMessage("solving subproblem: nstallnodes=%"SCIP_LONGINT_FORMAT", maxnodes=%"SCIP_LONGINT_FORMAT"\n", nstallnodes, maxnodes);
      retcode = SCIPsolve(subscip);

      /* Errors in solving the subproblem should not kill the overall solving process
       * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      {
#ifndef NDEBUG
         SCIP_CALL( retcode );
#endif
         SCIPwarningMessage(scip, "Error while solving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
      }

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      }
      if( success )
         *result = SCIP_FOUNDSOL;
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Example #4
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecLocalbranching)
{  /*lint --e{715}*/
   SCIP_Longint maxnnodes;                   /* maximum number of subnodes                            */
   SCIP_Longint nsubnodes;                   /* nodelimit for subscip                                 */

   SCIP_HEURDATA* heurdata;
   SCIP* subscip;                            /* the subproblem created by localbranching              */
   SCIP_VAR** subvars;                       /* subproblem's variables                                */
   SCIP_SOL* bestsol;                        /* best solution so far                                  */
   SCIP_EVENTHDLR*       eventhdlr;          /* event handler for LP events                     */

   SCIP_Real timelimit;                      /* timelimit for subscip (equals remaining time of scip) */
   SCIP_Real cutoff;                         /* objective cutoff for the subproblem                   */
   SCIP_Real upperbound;
   SCIP_Real memorylimit;

   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */
   SCIP_VAR** vars;

   int nvars;
   int i;

   SCIP_Bool success;

   SCIP_RETCODE retcode;

   assert(heur != NULL);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   /* get heuristic's data */
   heurdata = SCIPheurGetData(heur);
   assert( heurdata != NULL );

   /* there should be enough binary variables that a local branching constraint makes sense */
   if( SCIPgetNBinVars(scip) < 2*heurdata->neighborhoodsize )
      return SCIP_OKAY;

   *result = SCIP_DELAYED;

   /* only call heuristic, if an IP solution is at hand */
   if( SCIPgetNSols(scip) <= 0  )
      return SCIP_OKAY;

   bestsol = SCIPgetBestSol(scip);
   assert(bestsol != NULL);

   /* only call heuristic, if the best solution comes from transformed problem */
   if( SCIPsolIsOriginal(bestsol) )
      return SCIP_OKAY;

   /* only call heuristic, if enough nodes were processed since last incumbent */
   if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip, bestsol)  < heurdata->nwaitingnodes)
      return SCIP_OKAY;

   /* only call heuristic, if the best solution does not come from trivial heuristic */
   if( SCIPsolGetHeur(bestsol) != NULL && strcmp(SCIPheurGetName(SCIPsolGetHeur(bestsol)), "trivial") == 0 )
      return SCIP_OKAY;

   /* reset neighborhood and minnodes, if new solution was found */
   if( heurdata->lastsol != bestsol )
   {
      heurdata->curneighborhoodsize = heurdata->neighborhoodsize;
      heurdata->curminnodes = heurdata->minnodes;
      heurdata->emptyneighborhoodsize = 0;
      heurdata->callstatus = EXECUTE;
      heurdata->lastsol = bestsol;
   }

   /* if no new solution was found and local branching also seems to fail, just keep on waiting */
   if( heurdata->callstatus == WAITFORNEWSOL )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* calculate the maximal number of branching nodes until heuristic is aborted */
   maxnnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));

   /* reward local branching if it succeeded often */
   maxnnodes = (SCIP_Longint)(maxnnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
   maxnnodes -= 100 * SCIPheurGetNCalls(heur);  /* count the setup costs for the sub-MIP as 100 nodes */
   maxnnodes += heurdata->nodesofs;

   /* determine the node limit for the current process */
   nsubnodes = maxnnodes - heurdata->usednodes;
   nsubnodes = MIN(nsubnodes, heurdata->maxnodes);

   /* check whether we have enough nodes left to call sub problem solving */
   if( nsubnodes < heurdata->curminnodes )
      return SCIP_OKAY;

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIPdebugMessage("running localbranching heuristic ...\n");

   /* get the data of the variables and the best solution */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initializing the subproblem */
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;
   eventhdlr = NULL;

   if( heurdata->uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_localbranchsub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_localbranchsub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "localbranchsub", TRUE, FALSE, TRUE, &success) );

      if( heurdata->copycuts )
      {
         /* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }

      /* create event handler for LP events */
      SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecLocalbranching, NULL) );
      if( eventhdlr == NULL )
      {
         SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
         return SCIP_PLUGINNOTFOUND;
      }
   }
   SCIPdebugMessage("Copying the plugins was %ssuccessful.\n", success ? "" : "not ");

   for (i = 0; i < nvars; ++i)
      subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* if the subproblem could not be created, free memory and return */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;
      goto TERMINATE;
   }

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

#ifndef SCIP_DEBUG
   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif

   /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   heurdata->nodelimit = nsubnodes;
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", MAX(10, nsubnodes/10)) );
   SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", 3) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   if( !SCIPisParamFixed(subscip, "conflict/useprop") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usesb") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
   }

   /* employ a limit on the number of enforcement rounds in the quadratic constraint handler; this fixes the issue that
    * sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
    * feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
    * instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no deductions shall be
    * made for the original SCIP
    */
   if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 500) );
   }

   /* copy the original problem and add the local branching constraint */
   if( heurdata->uselprows )
   {
      SCIP_CALL( createSubproblem(scip, subscip, subvars) );
   }
   SCIP_CALL( addLocalBranchingConstraint(scip, subscip, subvars, heurdata) );

   /* add an objective cutoff */
   cutoff = SCIPinfinity(scip);
   assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );

   upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
   if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
   {
      cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
   }
   else
   {
      if( SCIPgetUpperbound ( scip ) >= 0 )
         cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
      else
         cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
   }
   cutoff = MIN(upperbound, cutoff );
   SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );

   /* catch LP events of sub-SCIP */
   if( !heurdata->uselprows )
   {
      assert(eventhdlr != NULL);

      SCIP_CALL( SCIPtransformProb(subscip) );
      SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
   }

   /* solve the subproblem */
   SCIPdebugMessage("solving local branching subproblem with neighborhoodsize %d and maxnodes %"SCIP_LONGINT_FORMAT"\n",
      heurdata->curneighborhoodsize, nsubnodes);
   retcode = SCIPsolve(subscip);

   /* drop LP events of sub-SCIP */
   if( !heurdata->uselprows )
   {
      assert(eventhdlr != NULL);

      SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );
   }

   /* Errors in solving the subproblem should not kill the overall solving process
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in local branching heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   /* print solving statistics of subproblem if we are in SCIP's debug mode */
   SCIPdebug( SCIP_CALL( SCIPprintStatistics(subscip, NULL) ) );

   heurdata->usednodes += SCIPgetNNodes(subscip);
   SCIPdebugMessage("local branching used %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT" nodes\n",
      SCIPgetNNodes(subscip), nsubnodes);

   /* check, whether a solution was found */
   if( SCIPgetNSols(subscip) > 0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      }
      if( success )
      {
         SCIPdebugMessage("-> accepted solution of value %g\n", SCIPgetSolOrigObj(subscip, subsols[i]));
         *result = SCIP_FOUNDSOL;
      }
   }

   /* check the status of the sub-MIP */
   switch( SCIPgetStatus(subscip) )
   {
   case SCIP_STATUS_OPTIMAL:
   case SCIP_STATUS_BESTSOLLIMIT:
      heurdata->callstatus = WAITFORNEWSOL; /* new solution will immediately be installed at next call */
      SCIPdebugMessage(" -> found new solution\n");
      break;

   case SCIP_STATUS_NODELIMIT:
   case SCIP_STATUS_STALLNODELIMIT:
   case SCIP_STATUS_TOTALNODELIMIT:
      heurdata->callstatus = EXECUTE;
      heurdata->curneighborhoodsize = (heurdata->emptyneighborhoodsize + heurdata->curneighborhoodsize)/2;
      heurdata->curminnodes *= 2;
      SCIPdebugMessage(" -> node limit reached: reduced neighborhood to %d, increased minnodes to %d\n",
         heurdata->curneighborhoodsize, heurdata->curminnodes);
      if( heurdata->curneighborhoodsize <= heurdata->emptyneighborhoodsize )
      {
         heurdata->callstatus = WAITFORNEWSOL;
         SCIPdebugMessage(" -> new neighborhood was already proven to be empty: wait for new solution\n");
      }
      break;

   case SCIP_STATUS_INFEASIBLE:
   case SCIP_STATUS_INFORUNBD:
      heurdata->emptyneighborhoodsize = heurdata->curneighborhoodsize;
      heurdata->curneighborhoodsize += heurdata->curneighborhoodsize/2;
      heurdata->curneighborhoodsize = MAX(heurdata->curneighborhoodsize, heurdata->emptyneighborhoodsize + 2);
      heurdata->callstatus = EXECUTE;
      SCIPdebugMessage(" -> neighborhood is empty: increased neighborhood to %d\n", heurdata->curneighborhoodsize);
      break;

   case SCIP_STATUS_UNKNOWN:
   case SCIP_STATUS_USERINTERRUPT:
   case SCIP_STATUS_TIMELIMIT:
   case SCIP_STATUS_MEMLIMIT:
   case SCIP_STATUS_GAPLIMIT:
   case SCIP_STATUS_SOLLIMIT:
   case SCIP_STATUS_UNBOUNDED:
   default:
      heurdata->callstatus = WAITFORNEWSOL;
      SCIPdebugMessage(" -> unexpected sub-MIP status <%d>: waiting for new solution\n", SCIPgetStatus(subscip));
      break;
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Example #5
0
/** branching execution method for fractional LP solutions */
static
SCIP_DECL_BRANCHEXECLP(branchExeclpStp)
{  /*lint --e{715}*/
   SCIP_PROBDATA* probdata;
   SCIP_CONS* consin;
   SCIP_CONS* consout;
   SCIP_NODE* vertexin;
   SCIP_NODE* vertexout;
   SCIP_VAR** edgevars;
   SCIP_Real estimatein;
   SCIP_Real estimateout;
   GRAPH* g;
   int e;
   int branchvertex;

   assert(branchrule != NULL);
   assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   SCIPdebugMessage("Execlp method of Stp branching\n ");
   estimatein = SCIPgetUpperbound(scip);
   estimateout = SCIPgetUpperbound(scip);
   *result = SCIP_DIDNOTRUN;

   /* get problem data */
   probdata = SCIPgetProbData(scip);
   assert(probdata != NULL);

   /* get graph */
   g = SCIPprobdataGetGraph(probdata);
   assert(g != NULL);


   /* get vertex to branch on */
   SCIP_CALL( selectBranchingVertex(scip, &branchvertex) );

   if( branchvertex == UNKNOWN )
   {
      SCIPdebugMessage("Branching did not run \n");
      return SCIP_OKAY;
   }

   edgevars = SCIPprobdataGetEdgeVars(scip);

   /* create constraints */
   SCIP_CALL( SCIPcreateConsLinear(scip, &consin, "consin", 0,
         NULL, NULL, 1.0, 1.0,
         TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE) );

   SCIP_CALL( SCIPcreateConsLinear(scip, &consout, "consout", 0,
         NULL, NULL, 0.0, 0.0,
         TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE) );

   for( e = g->inpbeg[branchvertex]; e != EAT_LAST; e = g->ieat[e] )
   {
      SCIP_CALL( SCIPaddCoefLinear(scip, consin,  edgevars[e], 1.0) );
      SCIP_CALL( SCIPaddCoefLinear(scip, consout, edgevars[e], 1.0) );
      SCIP_CALL( SCIPaddCoefLinear(scip, consout, edgevars[flipedge(e)], 1.0) );
   }

   /* create the child nodes */
   SCIP_CALL( SCIPcreateChild(scip, &vertexin, 1.0, estimatein) );

   SCIP_CALL( SCIPcreateChild(scip, &vertexout, 1.0, estimateout) );

   assert(vertexin != NULL);
   assert(vertexout != NULL);

   SCIP_CALL( SCIPaddConsNode(scip, vertexin, consin, NULL) );
   SCIP_CALL( SCIPaddConsNode(scip, vertexout, consout, NULL) );

   /* relase constraints */
   SCIP_CALL( SCIPreleaseCons(scip, &consin) );
   SCIP_CALL( SCIPreleaseCons(scip, &consout) );

   SCIPdebugMessage("Branched on stp vertex %d \n", branchvertex);

   *result = SCIP_BRANCHED;


   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecCrossover)
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;                  /* primal heuristic data                               */
   SCIP* subscip;                            /* the subproblem created by crossover                 */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */

   SCIP_VAR** vars;                          /* original problem's variables                        */
   SCIP_VAR** subvars;                       /* subproblem's variables                              */
   SCIP_SOL** sols;

   SCIP_Real memorylimit;                    /* memory limit for the subproblem                     */
   SCIP_Real timelimit;                      /* time limit for the subproblem                       */
   SCIP_Real cutoff;                         /* objective cutoff for the subproblem                 */
   SCIP_Real upperbound;
   SCIP_Bool success;

   SCIP_Longint nstallnodes;                 /* node limit for the subproblem                       */

   int* selection;                           /* pool of solutions crossover uses                    */
   int nvars;                                /* number of original problem's variables              */
   int nbinvars;
   int nintvars;
   int nusedsols;
   int i;

   SCIP_RETCODE retcode;

   assert(heur != NULL);
   assert(scip != NULL);
   assert(result != NULL);

   /* get heuristic's data */
   heurdata = SCIPheurGetData(heur);
   assert(heurdata != NULL);
   nusedsols = heurdata->nusedsols;

   *result = SCIP_DELAYED;

   /* only call heuristic, if enough solutions are at hand */
   if( SCIPgetNSols(scip) < nusedsols  )
      return SCIP_OKAY;

   sols = SCIPgetSols(scip);
   assert(sols != NULL);

   /* if one good solution was found, heuristic should not be delayed any longer */
   if( sols[nusedsols-1] != heurdata->prevlastsol )
   {
      heurdata->nextnodenumber = SCIPgetNNodes(scip);
      if( sols[0] != heurdata->prevbestsol )
         heurdata->nfailures = 0;
   }
   /* in nonrandomized mode: only recall heuristic, if at least one new good solution was found in the meantime */
   else if( !heurdata->randomization )
      return SCIP_OKAY;

   /* if heuristic should be delayed, wait until certain number of nodes is reached */
   if( SCIPgetNNodes(scip) < heurdata->nextnodenumber )
      return SCIP_OKAY;

   /* only call heuristic, if enough nodes were processed since last incumbent */
   if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip))  < heurdata->nwaitingnodes
      && (SCIPgetDepth(scip) > 0 || !heurdata->dontwaitatroot) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* calculate the maximal number of branching nodes until heuristic is aborted */
   nstallnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));

   /* reward Crossover if it succeeded often */
   nstallnodes = (SCIP_Longint)
      (nstallnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));

   /* count the setup costs for the sub-MIP as 100 nodes */
   nstallnodes -= 100 * SCIPheurGetNCalls(heur);
   nstallnodes += heurdata->nodesofs;

   /* determine the node limit for the current process */
   nstallnodes -= heurdata->usednodes;
   nstallnodes = MIN(nstallnodes, heurdata->maxnodes);

   /* check whether we have enough nodes left to call subproblem solving */
   if( nstallnodes < heurdata->minnodes )
      return SCIP_OKAY;

   if( SCIPisStopped(scip) )
     return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
   assert(nvars > 0);

   /* check whether discrete variables are available */
   if( nbinvars == 0 && nintvars == 0 )
      return SCIP_OKAY;

   /* initializing the subproblem */
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;

   if( heurdata->uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_crossoversub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_crossoversub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "crossover", TRUE, FALSE, TRUE, &success) );

      if( heurdata->copycuts )
      {
         /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }
   }

   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &selection, nusedsols) );

   for( i = 0; i < nvars; i++ )
     subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   success = FALSE;

   /* create a new problem, which fixes variables with same value in a certain set of solutions */
   SCIP_CALL( setupSubproblem(scip, subscip, subvars, selection, heurdata, &success) );

   heurdata->prevbestsol = SCIPgetBestSol(scip);
   heurdata->prevlastsol = sols[heurdata->nusedsols-1];

   /* if creation of sub-SCIP was aborted (e.g. due to number of fixings), free sub-SCIP and abort */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;

      /* this run will be counted as a failure since no new solution tuple could be generated or the neighborhood of the
       * solution was not fruitful in the sense that it was too big
       */
      updateFailureStatistic(scip, heurdata);

      goto TERMINATE;
   }

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

   /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nstallnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   if( !SCIPisParamFixed(subscip, "conflict/useprop") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usesb") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
   }

   /* add an objective cutoff */
   cutoff = SCIPinfinity(scip);
   assert(!SCIPisInfinity(scip, SCIPgetUpperbound(scip)));

   upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
   if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
   {
      cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
   }
   else
   {
      if( SCIPgetUpperbound ( scip ) >= 0 )
         cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
      else
         cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
   }
   cutoff = MIN(upperbound, cutoff );
   SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );

   /* permute the subproblem to increase diversification */
   if( heurdata->permute )
   {
      SCIP_CALL( SCIPpermuteProb(subscip, (unsigned int) SCIPheurGetNCalls(heur), TRUE, TRUE, TRUE, TRUE, TRUE) );
   }

   /* solve the subproblem */
   SCIPdebugMessage("Solve Crossover subMIP\n");
   retcode = SCIPsolve(subscip);

   /* Errors in solving the subproblem should not kill the overall solving process.
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in Crossover heuristic; sub-SCIP terminated with code <%d>\n", retcode);
   }

   heurdata->usednodes += SCIPgetNNodes(subscip);

   /* check, whether a solution was found */
   if( SCIPgetNSols(subscip) > 0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;
      int solindex;                             /* index of the solution created by crossover          */

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      solindex = -1;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &solindex, &success) );
      }

      if( success )
      {
         int tmp;

         assert(solindex != -1);

         *result = SCIP_FOUNDSOL;

         /* insert all crossings of the new solution and (nusedsols-1) of its parents into the hashtable
          * in order to avoid incest ;)
          */
         for( i = 0; i < nusedsols; i++ )
         {
            SOLTUPLE* elem;
            tmp = selection[i];
            selection[i] = solindex;

            SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
            SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
            selection[i] = tmp;
         }

         /* if solution was among the best ones, crossover should not be called until another good solution was found */
         if( !heurdata->randomization )
         {
            heurdata->prevbestsol = SCIPgetBestSol(scip);
            heurdata->prevlastsol = SCIPgetSols(scip)[heurdata->nusedsols-1];
         }
      }

      /* if solution is not better then incumbent or could not be added to problem => run is counted as a failure */
      if( !success || solindex != SCIPsolGetIndex(SCIPgetBestSol(scip)) )
         updateFailureStatistic(scip, heurdata);
   }
   else
   {
      /* if no new solution was found, run was a failure */
      updateFailureStatistic(scip, heurdata);
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &selection);
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpRapidlearning)
{/*lint --e{715}*/
   SCIP* subscip;                            /* the subproblem created by rapid learning       */
   SCIP_SEPADATA* sepadata;                  /* separator's private data                       */

   SCIP_VAR** vars;                          /* original problem's variables                   */
   SCIP_VAR** subvars;                       /* subproblem's variables                         */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */    
   SCIP_HASHMAP* varmapbw;                   /* mapping of sub-SCIP variables to SCIP variables */

   SCIP_CONSHDLR** conshdlrs;                /* array of constraint handler's that might that might obtain conflicts */
   int* oldnconss;                           /* number of constraints without rapid learning conflicts               */

   SCIP_Longint nodelimit;                   /* node limit for the subproblem                  */
   SCIP_Real timelimit;                      /* time limit for the subproblem                  */
   SCIP_Real memorylimit;                    /* memory limit for the subproblem                */

   int nconshdlrs;                           /* size of conshdlr and oldnconss array                      */
   int nfixedvars;                           /* number of variables that could be fixed by rapid learning */
   int nvars;                                /* number of variables                                       */           
   int restartnum;                           /* maximal number of conflicts that should be created        */
   int i;                                    /* counter                                                   */

   SCIP_Bool success;                        /* was problem creation / copying constraint successful? */
   SCIP_RETCODE retcode;                     /* used for catching sub-SCIP errors in debug mode */

   int nconflicts;                          /* statistic: number of conflicts applied         */
   int nbdchgs;                             /* statistic: number of bound changes applied     */
   int n1startinfers;                       /* statistic: number of one side infer values     */
   int n2startinfers;                       /* statistic: number of both side infer values    */

   SCIP_Bool soladded;                      /* statistic: was a new incumbent found?          */
   SCIP_Bool dualboundchg;                  /* statistic: was a new dual bound found?         */
   SCIP_Bool disabledualreductions;         /* TRUE, if dual reductions in sub-SCIP are not valid for original SCIP,
                                             * e.g., because a constraint could not be copied or a primal solution
                                             * could not be copied back 
                                             */

   int ndiscvars;

   soladded = FALSE;

   assert(sepa != NULL);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;
   
   ndiscvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip)+SCIPgetNImplVars(scip);

   /* only run when still not fixed binary variables exists */
   if( ndiscvars == 0 )
      return SCIP_OKAY;

   /* get separator's data */
   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   /* only run for integer programs */
   if( !sepadata->contvars && ndiscvars != SCIPgetNVars(scip) )
      return SCIP_OKAY;

   /* only run if there are few enough continuous variables */
   if( sepadata->contvars && SCIPgetNContVars(scip) > sepadata->contvarsquot * SCIPgetNVars(scip) )
      return SCIP_OKAY;

   /* do not run if pricers are present */
   if( SCIPgetNActivePricers(scip) > 0 )
      return SCIP_OKAY;

   /* if the separator should be exclusive to the root node, this prevents multiple calls due to restarts */
   if(  SCIPsepaGetFreq(sepa) == 0 && SCIPsepaGetNCalls(sepa) > 0)
      return SCIP_OKAY;

   /* call separator at most once per node */
   if( SCIPsepaGetNCallsAtNode(sepa) > 0 )
      return SCIP_OKAY;

   /* do not call rapid learning, if the problem is too big */
   if( SCIPgetNVars(scip) > sepadata->maxnvars || SCIPgetNConss(scip) > sepadata->maxnconss )
      return SCIP_OKAY; 

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;
   
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initializing the subproblem */  
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) ); 
   SCIP_CALL( SCIPcreate(&subscip) );
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;

   /* copy the subproblem */
   SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rapid", FALSE, FALSE, &success) );
   
   if( sepadata->copycuts )
   {
      /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
      SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, FALSE) );
   }

   for( i = 0; i < nvars; i++ )
      subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
   
   SCIPhashmapFree(&varmapfw);
   
   /* this avoids dual presolving */
   if( !success )
   {
      for( i = 0; i < nvars; i++ )
      {     
         SCIP_CALL( SCIPaddVarLocks(subscip, subvars[i], 1, 1 ) );
      }
   }

   SCIPdebugMessage("Copying SCIP was%s successful.\n", success ? "" : " not");
   
   /* mimic an FD solver: DFS, no LP solving, 1-FUIP instead of all-FUIP */
   SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
   SCIP_CALL( SCIPsetIntParam(subscip, "conflict/fuiplevels", 1) );
   SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) ); 
   SCIP_CALL( SCIPsetBoolParam(subscip, "constraints/disableenfops", TRUE) );
   SCIP_CALL( SCIPsetIntParam(subscip, "propagating/pseudoobj/freq", -1) );

   /* use inference branching */
   SCIP_CALL( SCIPsetBoolParam(subscip, "branching/inference/useweightedsum", FALSE) );

   /* only create short conflicts */
   SCIP_CALL( SCIPsetRealParam(subscip, "conflict/maxvarsfac", 0.05) );
  
   /* set limits for the subproblem */
   nodelimit = SCIPgetNLPIterations(scip);
   nodelimit = MAX(sepadata->minnodes, nodelimit);
   nodelimit = MIN(sepadata->maxnodes, nodelimit);

   restartnum = 1000;
   
   /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
   if( !SCIPisInfinity(scip, memorylimit) )   
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
   if( timelimit <= 0.0 || memorylimit <= 0.0 )
      goto TERMINATE;

   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit/5) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
   SCIP_CALL( SCIPsetIntParam(subscip, "limits/restarts", 0) );
   SCIP_CALL( SCIPsetIntParam(subscip, "conflict/restartnum", restartnum) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

#ifndef SCIP_DEBUG
   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif

   /* add an objective cutoff */
   SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetUpperbound(scip)) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapbw, SCIPblkmem(scip), SCIPcalcHashtableSize(5 * nvars)) );

   /* store reversing mapping of variables */
   SCIP_CALL( SCIPtransformProb(subscip) );
   for( i = 0; i < nvars; ++i)
   {  
      SCIP_CALL( SCIPhashmapInsert(varmapbw, SCIPvarGetTransVar(subvars[i]), vars[i]) );
   }

   /** allocate memory for constraints storage. Each constraint that will be created from now on will be a conflict.
    *  Therefore, we need to remember oldnconss to get the conflicts from the FD search. 
    */
   nconshdlrs = 4;
   SCIP_CALL( SCIPallocBufferArray(scip, &conshdlrs, nconshdlrs) );
   SCIP_CALL( SCIPallocBufferArray(scip, &oldnconss, nconshdlrs) );

   /* store number of constraints before rapid learning search */
   conshdlrs[0] = SCIPfindConshdlr(subscip, "bounddisjunction");
   conshdlrs[1] = SCIPfindConshdlr(subscip, "setppc");
   conshdlrs[2] = SCIPfindConshdlr(subscip, "linear");
   conshdlrs[3] = SCIPfindConshdlr(subscip, "logicor");

   /* redundant constraints might be eliminated in presolving */
   SCIP_CALL( SCIPpresolve(subscip));

   for( i = 0; i < nconshdlrs; ++i)
   {
      if( conshdlrs[i] != NULL )
         oldnconss[i] = SCIPconshdlrGetNConss(conshdlrs[i]);
   }

   nfixedvars = SCIPgetNFixedVars(scip);
   
   /* solve the subproblem */
   retcode = SCIPsolve(subscip);
   
   /* Errors in solving the subproblem should not kill the overall solving process 
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   { 
#ifndef NDEBUG
      SCIP_CALL( retcode );     
#endif
      SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
   }
 
   /* abort solving, if limit of applied conflicts is reached */
   if( SCIPgetNConflictConssApplied(subscip) >= restartnum )
   {
      SCIPdebugMessage("finish after %lld successful conflict calls.\n", SCIPgetNConflictConssApplied(subscip)); 
   }
   /* if the first 20% of the solution process were successful, proceed */
   else if( (sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPisFeasLT(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
      || (sepadata->applybdchgs && SCIPgetNFixedVars(subscip) > nfixedvars)
      || (sepadata->applyconflicts && SCIPgetNConflictConssApplied(subscip) > 0) ) 
   {
      SCIPdebugMessage("proceed solving after the first 20%% of the solution process, since:\n");

      if( SCIPgetNSols(subscip) > 0 && SCIPisFeasLE(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
      {
         SCIPdebugMessage("   - there was a better solution (%f < %f)\n",SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip));
      }
      if( SCIPgetNFixedVars(subscip) > nfixedvars )
      {
         SCIPdebugMessage("   - there were %d variables fixed\n", SCIPgetNFixedVars(scip)-nfixedvars );
      }
      if( SCIPgetNConflictConssFound(subscip) > 0 )
      {
         SCIPdebugMessage("   - there were %lld conflict constraints created\n", SCIPgetNConflictConssApplied(subscip));
      }

      /* set node limit to 100% */
      SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit) );

      /* solve the subproblem */
      retcode = SCIPsolve(subscip);
   
      /* Errors in solving the subproblem should not kill the overall solving process 
       * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      { 
#ifndef NDEBUG
         SCIP_CALL( retcode );     
#endif
         SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
      }
   }
   else
   {
      SCIPdebugMessage("do not proceed solving after the first 20%% of the solution process.\n");
   }

#ifdef SCIP_DEBUG
   SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif

   disabledualreductions = FALSE;

   /* check, whether a solution was found */
   if( sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPfindHeur(scip, "trysol") != NULL )
   {
      SCIP_HEUR* heurtrysol;
      SCIP_SOL** subsols;
      int nsubsols;

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until was declared to be feasible 
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      soladded = FALSE;
      heurtrysol = SCIPfindHeur(scip, "trysol");

      /* sequentially add solutions to trysol heuristic */
      for( i = 0; i < nsubsols && !soladded; ++i )
      {
         SCIPdebugMessage("Try to create new solution by copying subscip solution.\n");
         SCIP_CALL( createNewSol(scip, subscip, subvars, heurtrysol, subsols[i], &soladded) );
      }
      if( !soladded || !SCIPisEQ(scip, SCIPgetSolOrigObj(subscip, subsols[i-1]), SCIPgetSolOrigObj(subscip, subsols[0])) )
         disabledualreductions = TRUE;
   }

   /* if the sub problem was solved completely, we update the dual bound */
   dualboundchg = FALSE;
   if( sepadata->applysolved && !disabledualreductions 
      && (SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL || SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE) )
   {
      /* we need to multiply the dualbound with the scaling factor and add the offset, 
       * because this information has been disregarded in the sub-SCIP */
      SCIPdebugMessage("Update old dualbound %g to new dualbound %g.\n", SCIPgetDualbound(scip), SCIPgetTransObjscale(scip) * SCIPgetDualbound(subscip) + SCIPgetTransObjoffset(scip));

      SCIP_CALL( SCIPupdateLocalDualbound(scip, SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip)) );
      dualboundchg = TRUE;
   }

   /* check, whether conflicts were created */
   nconflicts = 0;
   if( sepadata->applyconflicts && !disabledualreductions && SCIPgetNConflictConssApplied(subscip) > 0 )
   {
      SCIP_HASHMAP* consmap;
      int hashtablesize;

      assert(SCIPgetNConflictConssApplied(subscip) < (SCIP_Longint) INT_MAX);
      hashtablesize = (int) SCIPgetNConflictConssApplied(subscip);
      assert(hashtablesize < INT_MAX/5);
      hashtablesize *= 5;

      /* create the variable mapping hash map */
      SCIP_CALL( SCIPhashmapCreate(&consmap, SCIPblkmem(scip), SCIPcalcHashtableSize(hashtablesize)) );

      /* loop over all constraint handlers that might contain conflict constraints */
      for( i = 0; i < nconshdlrs; ++i)
      {
         /* copy constraints that have been created in FD run */
         if( conshdlrs[i] != NULL && SCIPconshdlrGetNConss(conshdlrs[i]) > oldnconss[i] )
         {
            SCIP_CONS** conss;
            int c;
            int nconss;
            
            nconss = SCIPconshdlrGetNConss(conshdlrs[i]);
            conss = SCIPconshdlrGetConss(conshdlrs[i]);

            /* loop over all constraints that have been added in sub-SCIP run, these are the conflicts */            
            for( c = oldnconss[i]; c < nconss; ++c)
            {
               SCIP_CONS* cons;
               SCIP_CONS* conscopy;
               
               cons = conss[c];
               assert(cons != NULL);        

               success = FALSE;

               SCIP_CALL( SCIPgetConsCopy(subscip, scip, cons, &conscopy, conshdlrs[i], varmapbw, consmap, NULL,
                     SCIPconsIsInitial(cons), SCIPconsIsSeparated(cons), SCIPconsIsEnforced(cons), SCIPconsIsChecked(cons),
                     SCIPconsIsPropagated(cons), TRUE, FALSE, SCIPconsIsDynamic(cons), 
                     SCIPconsIsRemovable(cons), FALSE, TRUE, &success) );

               if( success )
               {
                  nconflicts++;
                  SCIP_CALL( SCIPaddCons(scip, conscopy) );
                  SCIP_CALL( SCIPreleaseCons(scip, &conscopy) );
               }
               else
               {
                  SCIPdebugMessage("failed to copy conflict constraint %s back to original SCIP\n", SCIPconsGetName(cons));
               }
            }
         }
      }   
      SCIPhashmapFree(&consmap);
   }

   /* check, whether tighter global bounds were detected */
   nbdchgs = 0;
   if( sepadata->applybdchgs && !disabledualreductions )
      for( i = 0; i < nvars; ++i )
      {
         SCIP_Bool infeasible;
         SCIP_Bool tightened;
         
         assert(SCIPisLE(scip, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetLbGlobal(subvars[i]))); 
         assert(SCIPisLE(scip, SCIPvarGetLbGlobal(subvars[i]), SCIPvarGetUbGlobal(subvars[i])));
         assert(SCIPisLE(scip, SCIPvarGetUbGlobal(subvars[i]), SCIPvarGetUbGlobal(vars[i])));  
         
         /* update the bounds of the original SCIP, if a better bound was proven in the sub-SCIP */
         SCIP_CALL( SCIPtightenVarUb(scip, vars[i], SCIPvarGetUbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
         if( tightened ) 
            nbdchgs++;
         
         SCIP_CALL( SCIPtightenVarLb(scip, vars[i], SCIPvarGetLbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
         if( tightened )
            nbdchgs++;   
      }

   n1startinfers = 0;
   n2startinfers = 0;

   /* install start values for inference branching */
   if( sepadata->applyinfervals && (!sepadata->reducedinfer || soladded || nbdchgs+nconflicts > 0) )
   {
      for( i = 0; i < nvars; ++i )
      {
         SCIP_Real downinfer;
         SCIP_Real upinfer;
         SCIP_Real downvsids;
         SCIP_Real upvsids;
         SCIP_Real downconflen;
         SCIP_Real upconflen;
        
         /* copy downwards branching statistics */
         downvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);            
         downconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
         downinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);            
         
         /* copy upwards branching statistics */
         upvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);                     
         upconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
         upinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);            
        
         /* memorize statistics */
         if( downinfer+downconflen+downvsids > 0.0 || upinfer+upconflen+upvsids != 0 )
            n1startinfers++;
         
         if( downinfer+downconflen+downvsids > 0.0 && upinfer+upconflen+upvsids != 0 )
            n2startinfers++;
         
         SCIP_CALL( SCIPinitVarBranchStats(scip, vars[i], 0.0, 0.0, downvsids, upvsids, downconflen, upconflen, downinfer, upinfer, 0.0, 0.0) );
      }   
   }
   
   SCIPdebugPrintf("XXX Rapidlearning added %d conflicts, changed %d bounds, %s primal solution, %s dual bound improvement.\n", nconflicts, nbdchgs, soladded ? "found" : "no", 
      dualboundchg ? "found" : "no");

   SCIPdebugPrintf("YYY Infervalues initialized on one side: %5.2f %% of variables, %5.2f %% on both sides\n", 
      100.0 * n1startinfers/(SCIP_Real)nvars, 100.0 * n2startinfers/(SCIP_Real)nvars);

   /* change result pointer */
   if( nconflicts > 0 || dualboundchg )
      *result = SCIP_CONSADDED;
   else if( nbdchgs > 0 )
      *result = SCIP_REDUCEDDOM;
  
   /* free local data */
   SCIPfreeBufferArray(scip, &oldnconss);
   SCIPfreeBufferArray(scip, &conshdlrs);

   SCIPhashmapFree(&varmapbw);

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );
  
   return SCIP_OKAY;
}