SolutionStatus ILPSolverSCIP::get_status() const
    {
        int n = 0; // There are null-pointer accesses if called in the wrong stage, which happens if resetted.
        switch (SCIPgetStage(d_scip))
        {
        case SCIP_STAGE_TRANSFORMED:  [[fallthrough]];
        case SCIP_STAGE_INITPRESOLVE: [[fallthrough]];
        case SCIP_STAGE_PRESOLVING:   [[fallthrough]];
        case SCIP_STAGE_EXITPRESOLVE: [[fallthrough]];
        case SCIP_STAGE_PRESOLVED:    [[fallthrough]];
        case SCIP_STAGE_INITSOLVE:    [[fallthrough]];
        case SCIP_STAGE_SOLVING:      [[fallthrough]];
        case SCIP_STAGE_SOLVED:       [[fallthrough]];
        case SCIP_STAGE_EXITSOLVE:
            n = static_cast<int>(SCIPgetNSolsFound(d_scip));
        }

        SolutionStatus ret = (n > 0) ? SolutionStatus::SUBOPTIMAL : SolutionStatus::NO_SOLUTION;

        // Handle all possible status values. Almost all will be reduced to SUBOPTIMAL or NO_SOLUTION.
        switch (SCIPgetStatus(d_scip))
        {
        case SCIP_STATUS_OPTIMAL:    return SolutionStatus::PROVEN_OPTIMAL;
        case SCIP_STATUS_INFEASIBLE: return SolutionStatus::PROVEN_INFEASIBLE;
        case SCIP_STATUS_UNBOUNDED:  return SolutionStatus::PROVEN_UNBOUNDED;
        case SCIP_STATUS_UNKNOWN:        [[fallthrough]];
        case SCIP_STATUS_INFORUNBD:      [[fallthrough]];
        case SCIP_STATUS_NODELIMIT:      [[fallthrough]];
        case SCIP_STATUS_TOTALNODELIMIT: [[fallthrough]];
        case SCIP_STATUS_STALLNODELIMIT: [[fallthrough]];
        case SCIP_STATUS_TIMELIMIT:      [[fallthrough]];
        case SCIP_STATUS_MEMLIMIT:       [[fallthrough]];
        case SCIP_STATUS_GAPLIMIT:       [[fallthrough]];
        case SCIP_STATUS_SOLLIMIT:       [[fallthrough]];
        case SCIP_STATUS_BESTSOLLIMIT:   [[fallthrough]];
        case SCIP_STATUS_RESTARTLIMIT:   [[fallthrough]];
        case SCIP_STATUS_USERINTERRUPT:  [[fallthrough]];
        case SCIP_STATUS_TERMINATE:      [[fallthrough]];
        default:                     return ret;
        }
    }
Example #2
0
int SCIPSolver::solve(){
  DBG("solve!%s\n", "");
  
  if(!has_been_added) initialise();

  if(_verbosity > 0 && _verbosity < 3){
    // Do nothing extra
  } else if(_verbosity >= 3){
    SCIP_CALL_EXC(SCIPprintOrigProblem(_scip, NULL, NULL, FALSE));
    // SCIP_CALL_EXC(SCIPwriteOrigProblem(_scip, "scip.lp", "lp", TRUE));
  } else {
      // disable scip output to stdout
    SCIP_CALL_EXC( SCIPsetMessagehdlr(_scip, NULL) );
  }

  SCIP_CALL_EXC( SCIPsolve(_scip) );
  SCIP_STATUS status = SCIPgetStatus(_scip);
 
  if( status == SCIP_STATUS_OPTIMAL ) return SAT;
  else if( status == SCIP_STATUS_INFEASIBLE ) return UNSAT;
  else return UNKNOWN;
}
Example #3
0
bool SCIPSolver::is_opt(){
  return SCIPgetStatus(_scip) == SCIP_STATUS_OPTIMAL;
}
Example #4
0
bool SCIPSolver::is_sat(){
  return !( SCIPgetStatus(_scip) == SCIP_STATUS_INFEASIBLE );
}
Example #5
0
/** call writing method */
static
SCIP_RETCODE writeBounds(
   SCIP*                 scip,               /**< SCIP data structure */
   FILE*                 file,               /**< file to write to or NULL */
   SCIP_Bool             writesubmipdualbound/**< write dualbounds of submip roots for all open nodes */
   )
{
   SCIP_NODE** opennodes;
   int nopennodes;
   int n;
   int v;

   assert(scip != NULL);

   nopennodes = -1;

#ifdef LONGSTATS
   SCIPinfoMessage(scip, file, "Status after %"SCIP_LONGINT_FORMAT" processed nodes (%d open)\n", SCIPgetNNodes(scip), SCIPgetNNodesLeft(scip));

   SCIPinfoMessage(scip, file, "Primalbound: %g\n", SCIPgetPrimalbound(scip));
   SCIPinfoMessage(scip, file, "Dualbound: %g\n", SCIPgetDualbound(scip));
#else
   SCIPinfoMessage(scip, file, "PB %g\n", SCIPgetPrimalbound(scip));
#endif

   /* get all open nodes and therefor print all dualbounds */
   for( v = 2; v >= 0; --v )
   {
      SCIP_NODE* node;

      switch( v )
      {
      case 2:
         SCIP_CALL( SCIPgetChildren(scip, &opennodes, &nopennodes) );
         break;
      case 1:
         SCIP_CALL( SCIPgetSiblings(scip, &opennodes, &nopennodes) );
         break;
      case 0:
         SCIP_CALL( SCIPgetLeaves(scip, &opennodes, &nopennodes) );
         break;
      default:
	 assert(0);
	 break;
      }
      assert(nopennodes >= 0);

      /* print all node information */
      for( n = nopennodes - 1; n >= 0 && !SCIPisStopped(scip); --n )
      {
         node = opennodes[n];

         if( writesubmipdualbound )
         {
            SCIP* subscip;
            SCIP_Bool valid;
            SCIP_HASHMAP* varmap;                     /* mapping of SCIP variables to sub-SCIP variables */
            SCIP_VAR** vars;                          /* original problem's variables                    */
            int nvars;
            SCIP_Real submipdb;
	    SCIP_Bool cutoff;

            SCIP_CALL( SCIPcreate(&subscip) );

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

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

            submipdb = SCIP_INVALID;
            valid = FALSE;
	    cutoff = FALSE;
            SCIP_CALL( SCIPcopy(scip, subscip, varmap, NULL, "__boundwriting", TRUE, FALSE, TRUE, &valid) );

            if( valid )
            {
               SCIP_VAR** branchvars;
               SCIP_Real* branchbounds;
               SCIP_BOUNDTYPE* boundtypes;
               int nbranchvars;
               int size;

               size = SCIPnodeGetDepth(node);

               /* allocate memory for all branching decisions */
               SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
               SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
               SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );

               /* we assume that we only have one branching decision at each node */
               SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );

               /* check if did not have enough memory */
               if( nbranchvars > size )
               {
                  size = nbranchvars;
                  SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
                  SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
                  SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );

                  /* now getting all information */
                  SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );
               }

               /* apply all changes to the submip */
               SCIP_CALL( applyDomainChanges(subscip, branchvars, branchbounds, boundtypes, nbranchvars, varmap) );

               /* free memory for all branching decisions */
               SCIPfreeBufferArray(scip, &boundtypes);
               SCIPfreeBufferArray(scip, &branchbounds);
               SCIPfreeBufferArray(scip, &branchvars);

	       /* 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) );
	       /* solve only root node */
	       SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );

	       /* set cutoffbound as objective limit for subscip */
	       SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetCutoffbound(scip)) );

	       SCIP_CALL( SCIPsolve(subscip) );

	       cutoff = (SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE);
	       submipdb = SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip);
	    }

#ifdef LONGSTATS
            SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g, nodesubmiprootdualbound: %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#else
	    SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#endif

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

            SCIP_CALL( SCIPfree(&subscip) );
         }
         else
         {
#ifdef LONGSTATS
            SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#else
            SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#endif
         }
      }
   }

#ifdef LONGSTATS
   SCIPinfoMessage(scip, file, "\n");
#endif

   return SCIP_OKAY;
}
Example #6
0
/** call writing method */
static
SCIP_RETCODE writeBoundsFocusNode(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_EVENTHDLRDATA*   eventhdlrdata       /**< event handler data */
   )
{
   FILE* file;
   SCIP_Bool writesubmipdualbound;
   SCIP_NODE* node;

   assert(scip != NULL);
   assert(eventhdlrdata != NULL);

   file = eventhdlrdata->file;
   writesubmipdualbound = eventhdlrdata->writesubmipdualbound;
   node = SCIPgetCurrentNode(scip);

   /* do not process probing nodes */
   if( SCIPnodeGetType(node) == SCIP_NODETYPE_PROBINGNODE )
      return SCIP_OKAY;

   /* do not process cutoff nodes */
   if( SCIPisInfinity(scip, SCIPgetNodeDualbound(scip, node)) )
      return SCIP_OKAY;

   if( !SCIPisEQ(scip, eventhdlrdata->lastpb, SCIPgetPrimalbound(scip)) )
   {
#ifdef LONGSTATS
      SCIPinfoMessage(scip, file, "Status after %"SCIP_LONGINT_FORMAT" processed nodes (%d open)\n", SCIPgetNNodes(scip), SCIPgetNNodesLeft(scip));

      SCIPinfoMessage(scip, file, "Primalbound: %g\n", SCIPgetPrimalbound(scip));
      SCIPinfoMessage(scip, file, "Dualbound: %g\n", SCIPgetDualbound(scip));
#else
      SCIPinfoMessage(scip, file, "PB %g\n", SCIPgetPrimalbound(scip));
#endif
      eventhdlrdata->lastpb = SCIPgetPrimalbound(scip);
   }

   if( writesubmipdualbound )
   {
      SCIP* subscip;
      SCIP_Bool valid;
      SCIP_Real submipdb;
      SCIP_Bool cutoff;

      SCIP_CALL( SCIPcreate(&subscip) );

      submipdb = SCIP_INVALID;
      valid = FALSE;
      cutoff = FALSE;
      SCIP_CALL( SCIPcopy(scip, subscip, NULL, NULL, "__boundwriting", FALSE, FALSE, TRUE, &valid) );

      if( valid )
      {
	 /* 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) );
	 /* solve only root node */
	 SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );

#if 0
	 /* disable heuristics in subscip */
	 SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
#endif

	 /* set cutoffbound as objective limit for subscip */
	 SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetCutoffbound(scip)) );

	 SCIP_CALL( SCIPsolve(subscip) );

	 cutoff = (SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE);
	 submipdb = SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip);
      }

#ifdef LONGSTATS
      SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g, nodesubmiprootdualbound: %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#else
      SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#endif

      SCIP_CALL( SCIPfree(&subscip) );
   }
   else
   {
#ifdef LONGSTATS
      SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#else
      SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#endif
   }

#ifdef LONGSTATS
   SCIPinfoMessage(scip, file, "\n");
#endif

   return SCIP_OKAY;
}
Example #7
0
/** reduced cost pricing method of variable pricer for feasible LPs */
static
SCIP_DECL_PRICERREDCOST(pricerRedcostBinpacking)
{  /*lint --e{715}*/
   SCIP* subscip;
   SCIP_PRICERDATA* pricerdata;
   SCIP_CONS** conss;
   SCIP_VAR** vars;
   int* ids;
   SCIP_Bool addvar;

   SCIP_SOL** sols;
   int nsols;
   int s;

   int nitems;
   SCIP_Longint capacity;

   SCIP_Real timelimit;
   SCIP_Real memorylimit;

   assert(scip != NULL);
   assert(pricer != NULL);

   (*result) = SCIP_DIDNOTRUN;

   /* get the pricer data */
   pricerdata = SCIPpricerGetData(pricer);
   assert(pricerdata != NULL);

   capacity = pricerdata->capacity;
   conss = pricerdata->conss;
   ids = pricerdata->ids;
   nitems = pricerdata->nitems;

   /* get the remaining time and memory limit */
   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;

   /* initialize SCIP */
   SCIP_CALL( SCIPcreate(&subscip) );
   SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

   /* create problem in sub SCIP */
   SCIP_CALL( SCIPcreateProbBasic(subscip, "pricing") );
   SCIP_CALL( SCIPsetObjsense(subscip, SCIP_OBJSENSE_MAXIMIZE) );

   /* 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 time and memory limit */
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   SCIP_CALL( SCIPallocMemoryArray(subscip, &vars, nitems) );

   /* initialization local pricing problem */
   SCIP_CALL( initPricing(scip, pricerdata, subscip, vars) );

   SCIPdebugMessage("solve pricer problem\n");

   /* solve sub SCIP */
   SCIP_CALL( SCIPsolve(subscip) );

   sols = SCIPgetSols(subscip);
   nsols = SCIPgetNSols(subscip);
   addvar = FALSE;

   /* loop over all solutions and create the corresponding column to master if the reduced cost are negative for master,
    * that is the objective value i greater than 1.0
    */
   for( s = 0; s < nsols; ++s )
   {
      SCIP_Bool feasible;
      SCIP_SOL* sol;

      /* the soultion should be sorted w.r.t. the objective function value */
      assert(s == 0 || SCIPisFeasGE(subscip, SCIPgetSolOrigObj(subscip, sols[s-1]), SCIPgetSolOrigObj(subscip, sols[s])));

      sol = sols[s];
      assert(sol != NULL);

      /* check if solution is feasible in original sub SCIP */
      SCIP_CALL( SCIPcheckSolOrig(subscip, sol, &feasible, FALSE, FALSE ) );

      if( !feasible )
      {
         SCIPwarningMessage(scip, "solution in pricing problem (capacity <%d>) is infeasible\n", capacity);
         continue;
      }

      /* check if the solution has a value greater than 1.0 */
      if( SCIPisFeasGT(subscip, SCIPgetSolOrigObj(subscip, sol), 1.0) )
      {
         SCIP_VAR* var;
         SCIP_VARDATA* vardata;
         int* consids;
         char strtmp[SCIP_MAXSTRLEN];
         char name[SCIP_MAXSTRLEN];
         int nconss;
         int o;
         int v;

         SCIPdebug( SCIP_CALL( SCIPprintSol(subscip, sol, NULL, FALSE) ) );

         nconss = 0;
         (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "items");

         SCIP_CALL( SCIPallocBufferArray(scip, &consids, nitems) );

         /* check which variables are fixed -> which item belongs to this packing */
         for( o = 0, v = 0; o < nitems; ++o )
         {
            if( !SCIPconsIsEnabled(conss[o]) )
               continue;

            assert(SCIPgetNFixedonesSetppc(scip, conss[o]) == 0);

            if( SCIPgetSolVal(subscip, sol, vars[v]) > 0.5 )
            {
               (void) SCIPsnprintf(strtmp, SCIP_MAXSTRLEN, "_%d", ids[o]);
               strcat(name, strtmp);

               consids[nconss] = o;
               nconss++;
            }
            else
               assert( SCIPisFeasEQ(subscip, SCIPgetSolVal(subscip, sol, vars[v]), 0.0) );

            v++;
         }

         SCIP_CALL( SCIPvardataCreateBinpacking(scip, &vardata, consids, nconss) );

         /* create variable for a new column with objective function coefficient 0.0 */
         SCIP_CALL( SCIPcreateVarBinpacking(scip, &var, name, 1.0, FALSE, TRUE, vardata) );

         /* add the new variable to the pricer store */
         SCIP_CALL( SCIPaddPricedVar(scip, var, 1.0) );
         addvar = TRUE;

         /* change the upper bound of the binary variable to lazy since the upper bound is already enforced due to
          * the objective function the set covering constraint; The reason for doing is that, is to avoid the bound
          * of x <= 1 in the LP relaxation since this bound constraint would produce a dual variable which might have
          * a positive reduced cost
          */
         SCIP_CALL( SCIPchgVarUbLazy(scip, var, 1.0) );

         /* check which variable are fixed -> which orders belong to this packing */
         for( v = 0; v < nconss; ++v )
         {
            assert(SCIPconsIsEnabled(conss[consids[v]]));
            SCIP_CALL( SCIPaddCoefSetppc(scip, conss[consids[v]], var) );
         }

         SCIPdebug(SCIPprintVar(scip, var, NULL) );
         SCIP_CALL( SCIPreleaseVar(scip, &var) );

         SCIPfreeBufferArray(scip, &consids);
      }
      else
         break;
   }

   /* free pricer MIP */
   SCIPfreeMemoryArray(subscip, &vars);

   if( addvar || SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL )
      (*result) = SCIP_SUCCESS;

   /* free sub SCIP */
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Example #8
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;
}
/** 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;
}