Example #1
0
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
   SCIP*                 scip,               /**< original SCIP data structure */
   SCIP_HEUR*            heur,               /**< the current heuristic */
   SCIP_SOL*             sol,                /**< solution of the subproblem */
   SCIP_Bool*            success             /**< used to store whether new solution was found or not */
   )
{
   SCIP_VAR** vars;                          /* the original problem's variables */
   int        nvars;                         /* the original problem's number of variables */
   SCIP_Real* solvals;                       /* solution values of the subproblem */
   SCIP_SOL*  newsol;                        /* solution to be created for the original problem */

   assert(scip != NULL);

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

   SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );

   /* copy the solution */
   SCIP_CALL( SCIPgetSolVals(scip, sol, nvars, vars, solvals) );

   /* create new solution for the original problem */
   SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
   SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, solvals) );

   /* try to add new solution to scip and free it immediately */
   SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );

   SCIPfreeBufferArray(scip, &solvals);

   return SCIP_OKAY;
}
Example #2
0
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpImpliedbounds)
{  /*lint --e{715}*/
   SCIP_VAR** vars;
   SCIP_VAR** fracvars;
   SCIP_Real* solvals;
   SCIP_Real* fracvals;
   SCIP_Bool cutoff;
   int nvars;
   int nbinvars;
   int nfracs;
   int ncuts;

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

   *result = SCIP_DIDNOTRUN;

   /* gets active problem variables */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
   if( nbinvars == 0 )
      return SCIP_OKAY;

   /* get fractional problem variables */
   /* todo try out also separating fractional implicit integer variables */
   SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, &fracvals, NULL, &nfracs, NULL, NULL) );
   if( nfracs == 0 )
      return SCIP_OKAY;

   /* get solution values for all variables */
   SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
   SCIP_CALL( SCIPgetVarSols(scip, nvars, vars, solvals) );

   /* call the cut separation */
   SCIP_CALL( separateCuts(scip, sepa, NULL, solvals, fracvars, fracvals, nfracs, &cutoff, &ncuts) );

   /* adjust result code */
   if ( cutoff )
      *result = SCIP_CUTOFF;
   else if ( ncuts > 0 )
      *result = SCIP_SEPARATED;
   else
      *result = SCIP_DIDNOTFIND;

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &solvals);

   return SCIP_OKAY;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
   SCIP*                 scip,               /**< original SCIP data structure */
   SCIP*                 subscip,            /**< SCIP structure of the subproblem */
   SCIP_VAR**            subvars,            /**< the variables of the subproblem */
   SCIP_HEUR*            heur,               /**< crossover heuristic structure */
   SCIP_SOL*             subsol,             /**< solution of the subproblem */
   int*                  solindex,           /**< index of the solution */
   SCIP_Bool*            success             /**< used to store whether new solution was found or not */
   )
{
   SCIP_VAR** vars;                          /* the original problem's variables                */
   int        nvars;
   SCIP_SOL*  newsol;                        /* solution to be created for the original problem */
   SCIP_Real* subsolvals;                    /* solution values of the subproblem               */

   assert(scip != NULL);
   assert(subscip != NULL);
   assert(subvars != NULL);
   assert(subsol != NULL);

   /* get variables' data */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
   /* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
    * since constraint copying may have required the copy of variables that are fixed in the main SCIP
    */
   assert(nvars <= SCIPgetNOrigVars(subscip));

   SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );

   /* copy the solution */
   SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );

   /* create new solution for the original problem */
   SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
   SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
   *solindex = SCIPsolGetIndex(newsol);

   /* try to add new solution to scip and free it immediately */
   SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );

   SCIPfreeBufferArray(scip, &subsolvals);

   return SCIP_OKAY;
}
Example #4
0
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
   SCIP*                 scip,               /**< SCIP data structure  of the original problem      */
   SCIP*                 subscip,            /**< SCIP data structure  of the subproblem            */
   SCIP_VAR**            subvars,            /**< the variables of the subproblem                     */
   SCIP_HEUR*            heur,               /**< the Localbranching heuristic                      */
   SCIP_SOL*             subsol,             /**< solution of the subproblem                          */
   SCIP_Bool*            success             /**< pointer to store, whether new solution was found  */
   )
{
   SCIP_VAR** vars;
   int nvars;
   SCIP_SOL* newsol;
   SCIP_Real* subsolvals;

   assert( scip != NULL );
   assert( subscip != NULL );
   assert( subvars != NULL );
   assert( subsol != NULL );

   /* copy the solution */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
   /* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
    * since constraint copying may have required the copy of variables that are fixed in the main SCIP
    */
   assert(nvars <= SCIPgetNOrigVars(subscip));

   SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );

   /* copy the solution */
   SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );

   /* create new solution for the original problem */
   SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
   SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );

   SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );

   SCIPfreeBufferArray(scip, &subsolvals);

   return SCIP_OKAY;
}
Example #5
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;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpGomory)
{  /*lint --e{715}*/
   SCIP_SEPADATA* sepadata;
   SCIP_VAR** vars;
   SCIP_COL** cols;
   SCIP_ROW** rows;
   SCIP_Real* binvrow;
   SCIP_Real* cutcoefs;
   SCIP_Real maxscale;
   SCIP_Real minfrac;
   SCIP_Real maxfrac;
   SCIP_Longint maxdnom;
   SCIP_Bool cutoff;
   int* basisind;
   int naddedcuts;
   int nvars;
   int ncols;
   int nrows;
   int ncalls;
   int depth;
   int maxdepth;
   int maxsepacuts;
   int c;
   int i;

   assert(sepa != NULL);
   assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   depth = SCIPgetDepth(scip);
   ncalls = SCIPsepaGetNCallsAtNode(sepa);

   minfrac = sepadata->away;
   maxfrac = 1.0 - sepadata->away;

   /* only call separator, if we are not close to terminating */
   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only call the gomory cut separator a given number of times at each node */
   if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
      || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
      return SCIP_OKAY;

   /* only call separator, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call separator, if the LP solution is basic */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* only call separator, if there are fractional variables */
   if( SCIPgetNLPBranchCands(scip) == 0 )
      return SCIP_OKAY;

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

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
   if( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
   if( ncols >= 50*nrows )
      return SCIP_OKAY;

   if( ncols >= 5*nrows )
   {
      int ncutsfound;

      ncutsfound = SCIPgetNCutsFound(scip);
      if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
      {
         sepadata->lastncutsfound = ncutsfound;
         *result = SCIP_DELAYED;
         return SCIP_OKAY;
      }
   }
#endif

   /* set the maximal denominator in rational representation of gomory cut and the maximal scale factor to
    * scale resulting cut to integral values to avoid numerical instabilities
    */
   /**@todo find better but still stable gomory cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
   maxdepth = SCIPgetMaxDepth(scip);
   if( depth == 0 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/4 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/2 )
   {
      maxdnom = 100;
      maxscale = 100.0;
   }
   else
   {
      maxdnom = 10;
      maxscale = 10.0;
   }

   /* allocate temporary memory */
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );

   /* get basis indices */
   SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );

   /* get the maximal number of cuts allowed in a separation round */
   if( depth == 0 )
      maxsepacuts = sepadata->maxsepacutsroot;
   else
      maxsepacuts = sepadata->maxsepacuts;

   SCIPdebugMessage("searching gomory cuts: %d cols, %d rows, maxdnom=%"SCIP_LONGINT_FORMAT", maxscale=%g, maxcuts=%d\n",
      ncols, nrows, maxdnom, maxscale, maxsepacuts);

   cutoff = FALSE;
   naddedcuts = 0;

   /* for all basic columns belonging to integer variables, try to generate a gomory cut */
   for( i = 0; i < nrows && naddedcuts < maxsepacuts && !SCIPisStopped(scip) && !cutoff; ++i )
   {
      SCIP_Bool tryrow;

      tryrow = FALSE;
      c = basisind[i];
      if( c >= 0 )
      {
         SCIP_VAR* var;

         assert(c < ncols);
         var = SCIPcolGetVar(cols[c]);
         if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
         {
            SCIP_Real primsol;

            primsol = SCIPcolGetPrimsol(cols[c]);
            assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/

            if( SCIPfeasFrac(scip, primsol) >= minfrac )
            {
               SCIPdebugMessage("trying gomory cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
               tryrow = TRUE;
            }
         }
      }
      else if( sepadata->separaterows )
      {
         SCIP_ROW* row;

         assert(0 <= -c-1 && -c-1 < nrows);
         row = rows[-c-1];
         if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
         {
            SCIP_Real primsol;

            primsol = SCIPgetRowActivity(scip, row);
            if( SCIPfeasFrac(scip, primsol) >= minfrac )
            {
               SCIPdebugMessage("trying gomory cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
               tryrow = TRUE;
            }
         }
      }

      if( tryrow )
      {
         SCIP_Real cutrhs;
         SCIP_Real cutact;
         SCIP_Bool success;
         SCIP_Bool cutislocal;

         /* get the row of B^-1 for this basic integer variable with fractional solution value */
         SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow) );

         cutact = 0.0;
         cutrhs = SCIPinfinity(scip);

         /* create a MIR cut out of the weighted LP rows using the B^-1 row as weights */
         SCIP_CALL( SCIPcalcMIR(scip, NULL, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, FIXINTEGRALRHS, NULL, NULL,
               (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, minfrac, maxfrac,
               binvrow, 1.0, NULL, NULL, cutcoefs, &cutrhs, &cutact, &success, &cutislocal) );
         assert(ALLOWLOCAL || !cutislocal);

         /* @todo Currently we are using the SCIPcalcMIR() function to compute the coefficients of the Gomory
          *       cut. Alternatively, we could use the direct version (see thesis of Achterberg formula (8.4)) which
          *       leads to cut a of the form \sum a_i x_i \geq 1. Rumor has it that these cuts are better.
          */

         SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);

         /* if successful, convert dense cut into sparse row, and add the row as a cut */
         if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
         {
            SCIP_ROW* cut;
            char cutname[SCIP_MAXSTRLEN];
            int v;

            /* construct cut name */
            if( c >= 0 )
               (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_x%d", SCIPgetNLPs(scip), c);
            else
               (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_s%d", SCIPgetNLPs(scip), -c-1);

            /* create empty cut */
            SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs,
                  cutislocal, FALSE, sepadata->dynamiccuts) );

            /* cache the row extension and only flush them if the cut gets added */
            SCIP_CALL( SCIPcacheRowExtensions(scip, cut) );

            /* collect all non-zero coefficients */
            for( v = 0; v < nvars; ++v )
            {
               if( !SCIPisZero(scip, cutcoefs[v]) )
               {
                  SCIP_CALL( SCIPaddVarToRow(scip, cut, vars[v], cutcoefs[v]) );
               }
            }

            if( SCIProwGetNNonz(cut) == 0 )
            {
               assert(SCIPisFeasNegative(scip, cutrhs));
               SCIPdebugMessage(" -> gomory cut detected infeasibility with cut 0 <= %f\n", cutrhs);
               cutoff = TRUE;
            }
            else if( SCIProwGetNNonz(cut) == 1 )
            {
               /* add the bound change as cut to avoid that the LP gets modified. that would mean the LP is not flushed
                * and the method SCIPgetLPBInvRow() fails; SCIP internally will apply that bound change automatically
                */
               SCIP_CALL( SCIPaddCut(scip, NULL, cut, TRUE) );
               naddedcuts++;
            }
            else
            {
               /* Only take efficacious cuts, except for cuts with one non-zero coefficients (= bound
                * changes); the latter cuts will be handeled internally in sepastore.
                */
               if( SCIPisCutEfficacious(scip, NULL, cut) )
               {
                  assert(success == TRUE);

                  SCIPdebugMessage(" -> gomory cut for <%s>: act=%f, rhs=%f, eff=%f\n",
                     c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
                     cutact, cutrhs, SCIPgetCutEfficacy(scip, NULL, cut));

                  if( sepadata->makeintegral )
                  {
                     /* try to scale the cut to integral values */
                     SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                           maxdnom, maxscale, MAKECONTINTEGRAL, &success) );

                     if( sepadata->forcecuts )
                        success = TRUE;

                     /* in case the left hand side in minus infinity and the right hand side is plus infinity the cut is
                      * useless so we are not taking it at all
                      */
                     if( (SCIPisInfinity(scip, -SCIProwGetLhs(cut)) && SCIPisInfinity(scip, SCIProwGetRhs(cut))) )
                        success = FALSE;

                     /* @todo Trying to make the Gomory cut integral might fail. Due to numerical reasons/arguments we
                      *       currently ignore such cuts. If the cut, however, has small support (let's say smaller or equal to
                      *       5), we might want to add that cut (even it does not have integral coefficients). To be able to
                      *       do that we need to add a rank to the data structure of a row. The rank of original rows are
                      *       zero and for aggregated rows it is the maximum over all used rows plus one.
                      */
                  }

                  if( success )
                  {
                     SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut),
                        SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
                        SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));

                     /* flush all changes before adding the cut */
                     SCIP_CALL( SCIPflushRowExtensions(scip, cut) );

                     /* add global cuts which are not implicit bound changes to the cut pool */
                     if( !cutislocal )
                     {
                        if( sepadata->delayedcuts )
                        {
                           SCIP_CALL( SCIPaddDelayedPoolCut(scip, cut) );
                        }
                        else
                        {
                           SCIP_CALL( SCIPaddPoolCut(scip, cut) );
                        }
                     }
                     else
                     {
                        /* local cuts we add to the sepastore */
                        SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE) );
                     }

                     naddedcuts++;
                  }
               }
            }

            /* release the row */
            SCIP_CALL( SCIPreleaseRow(scip, &cut) );
         }
      }
   }

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &binvrow);
   SCIPfreeBufferArray(scip, &basisind);
   SCIPfreeBufferArray(scip, &cutcoefs);

   SCIPdebugMessage("end searching gomory cuts: found %d cuts\n", naddedcuts);

   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   /* evalute the result of the separation */
   if( cutoff )
      *result = SCIP_CUTOFF;
   else if ( naddedcuts > 0 )
      *result = SCIP_SEPARATED;
   else
      *result = SCIP_DIDNOTFIND;

   return SCIP_OKAY;
}
Example #7
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 #8
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 #9
0
/** transforms given solution of the master problem into solution of the original problem
 *  @todo think about types of epsilons used in this method
 */
SCIP_RETCODE GCGrelaxTransformMastersolToOrigsol(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_SOL*             mastersol,          /**< solution of the master problem, or NULL for current LP solution */
   SCIP_SOL**            origsol             /**< pointer to store the new created original problem's solution */
   )
{
   SCIP* masterprob;
   int npricingprobs;
   int* blocknrs;
   SCIP_Real* blockvalue;
   SCIP_Real increaseval;
   SCIP_VAR** mastervars;
   SCIP_Real* mastervals;
   int nmastervars;
   SCIP_VAR** vars;
   int nvars;
   SCIP_Real feastol;
   int i;
   int j;

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

   masterprob = GCGrelaxGetMasterprob(scip);
   npricingprobs = GCGrelaxGetNPricingprobs(scip);

   assert( !SCIPisInfinity(scip, SCIPgetSolOrigObj(masterprob, mastersol)) );
   
   SCIP_CALL( SCIPcreateSol(scip, origsol, GCGrelaxGetProbingheur(scip)) );

   SCIP_CALL( SCIPallocBufferArray(scip, &blockvalue, npricingprobs) );
   SCIP_CALL( SCIPallocBufferArray(scip, &blocknrs, npricingprobs) );

   /* get variables of the master problem and their solution values */
   SCIP_CALL( SCIPgetVarsData(masterprob, &mastervars, &nmastervars, NULL, NULL, NULL, NULL) );
   assert(mastervars != NULL);
   assert(nmastervars >= 0);

   SCIP_CALL( SCIPallocBufferArray(scip, &mastervals, nmastervars) );
   SCIP_CALL( SCIPgetSolVals(masterprob, mastersol, nmastervars, mastervars, mastervals) );

   /* initialize the block values for the pricing problems */
   for( i = 0; i < npricingprobs; i++ )
   {
      blockvalue[i] = 0.0;
      blocknrs[i] = 0;
   }

   /* loop over all given master variables */
   for( i = 0; i < nmastervars; i++ )
   {
      SCIP_VAR** origvars;
      int norigvars;
      SCIP_Real* origvals;
      SCIP_Bool isray;
      int blocknr;

      origvars = GCGmasterVarGetOrigvars(mastervars[i]);
      norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
      origvals = GCGmasterVarGetOrigvals(mastervars[i]);
      blocknr = GCGvarGetBlock(mastervars[i]);
      isray = GCGmasterVarIsRay(mastervars[i]);

      assert(GCGvarIsMaster(mastervars[i]));
      assert(!SCIPisFeasNegative(scip, mastervals[i]));

      /** @todo handle infinite master solution values */
      assert(!SCIPisInfinity(scip, mastervals[i]));

      /* first of all, handle variables representing rays */
      if( isray )
      {
         assert(blocknr >= 0);
         /* we also want to take into account variables representing rays, that have a small value (between normal and feas eps),
          * so we do no feas comparison here */
         if( SCIPisPositive(scip, mastervals[i]) )
         {
            /* loop over all original variables contained in the current master variable */
            for( j = 0; j < norigvars; j++ )
            {
               if( SCIPisZero(scip, origvals[j]) )
                  break;

               assert(!SCIPisZero(scip, origvals[j]));

               /* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done later) */
               if( GCGvarIsLinking(origvars[j]) )
                  continue;

               SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[j]), origvals[j] * mastervals[i], SCIPvarGetName(mastervars[i]));
               /* increase the corresponding value */
               SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[j], origvals[j] * mastervals[i]) );
            }
         }
         mastervals[i] = 0.0;
         continue;
      }

      /* handle the variables with value >= 1 to get integral values in original solution */
      while( SCIPisFeasGE(scip, mastervals[i], 1.0) )
      {
         /* variable was directly transferred to the master problem (only in linking conss or linking variable) */
         /** @todo this may be the wrong place for this case, handle it before the while loop
          * and remove the similar case in the next while loop */
         if( blocknr == -1 )
         {
            assert(norigvars == 1);
            assert(origvals[0] == 1.0);

            /* increase the corresponding value */
            SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i],  SCIPvarGetName(mastervars[i]));
            SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
            mastervals[i] = 0.0;
         }
         else
         {
            assert(blocknr >= 0);
            /* loop over all original variables contained in the current master variable */
            for( j = 0; j < norigvars; j++ )
            {
               SCIP_VAR* pricingvar;
               int norigpricingvars;
               SCIP_VAR** origpricingvars;
               if( SCIPisZero(scip, origvals[j]) )
                  break;
               assert(!SCIPisZero(scip, origvals[j]));

               /* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
               if( GCGvarIsLinking(origvars[j]) )
                  continue;

               pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
               assert(GCGvarIsPricing(pricingvar));

               norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
               origpricingvars = GCGpricingVarGetOrigvars(pricingvar);

               /* just in case a variable has a value higher than the number of blocks, it represents */
               if( norigpricingvars <= blocknrs[blocknr] )
               {
                  SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), mastervals[i] * origvals[j], SCIPvarGetName(mastervars[i]));
                  /* increase the corresponding value */
                  SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], mastervals[i] * origvals[j]) );
                  mastervals[i] = 1.0;
               }
               /* this should be default */
               else
               {
                  SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j], SCIPvarGetName(mastervars[i]) );
                  /* increase the corresponding value */
                  SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j]) );
               }
            }
            mastervals[i] = mastervals[i] - 1.0;
            blocknrs[blocknr]++;
         }
      }
   }

   /* loop over all given master variables */
   for( i = 0; i < nmastervars; i++ )
   {
      SCIP_VAR** origvars;
      int norigvars;
      SCIP_Real* origvals;
      int blocknr;

      origvars = GCGmasterVarGetOrigvars(mastervars[i]);
      norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
      origvals = GCGmasterVarGetOrigvals(mastervars[i]);
      blocknr = GCGvarGetBlock(mastervars[i]);

      if( SCIPisFeasZero(scip, mastervals[i]) )
      {
         continue;
      }
      assert(SCIPisFeasGE(scip, mastervals[i], 0.0) && SCIPisFeasLT(scip, mastervals[i], 1.0));

      while( SCIPisFeasPositive(scip, mastervals[i]) )
      {
         assert(GCGvarIsMaster(mastervars[i]));
         assert(!GCGmasterVarIsRay(mastervars[i]));

         if( blocknr == -1 )
         {
            assert(norigvars == 1);
            assert(origvals[0] == 1.0);

            SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]) );
            /* increase the corresponding value */
            SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
            mastervals[i] = 0.0;
         }
         else
         {
            increaseval = MIN(mastervals[i], 1.0 - blockvalue[blocknr]);
            /* loop over all original variables contained in the current master variable */
            for( j = 0; j < norigvars; j++ )
            {
               SCIP_VAR* pricingvar;
               int norigpricingvars;
               SCIP_VAR** origpricingvars;

               if( SCIPisZero(scip, origvals[j]) )
                  continue;

               /* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
               if( GCGvarIsLinking(origvars[j]) )
                  continue;

               pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
               assert(GCGvarIsPricing(pricingvar));

               norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
               origpricingvars = GCGpricingVarGetOrigvars(pricingvar);

               if( norigpricingvars <= blocknrs[blocknr] )
               {
                  increaseval = mastervals[i];

                  SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
                  /* increase the corresponding value */
                  SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], origvals[j] * increaseval) );
               }
               else
               {
                  /* increase the corresponding value */
                  SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
                  SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j] * increaseval) );
               }
            }

            mastervals[i] = mastervals[i] - increaseval;
            if( SCIPisFeasZero(scip, mastervals[i]) )
            {
               mastervals[i] = 0.0;
            }
            blockvalue[blocknr] += increaseval;

            /* if the value assigned to the block is equal to 1, this block is full and we take the next block */
            if( SCIPisFeasGE(scip, blockvalue[blocknr], 1.0) )
            {
               blockvalue[blocknr] = 0.0;
               blocknrs[blocknr]++;
            }
         }
      }
   }

   SCIPfreeBufferArray(scip, &mastervals);
   SCIPfreeBufferArray(scip, &blocknrs);
   SCIPfreeBufferArray(scip, &blockvalue);

   /* if the solution violates one of its bounds by more than feastol
    * and less than 10*feastol, round it and print a warning
    */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
   SCIP_CALL( SCIPgetRealParam(scip, "numerics/feastol", &feastol) );
   for( i = 0; i < nvars; ++i )
   {
      SCIP_Real solval;
      SCIP_Real lb;
      SCIP_Real ub;

      solval = SCIPgetSolVal(scip, *origsol, vars[i]);
      lb = SCIPvarGetLbLocal(vars[i]);
      ub = SCIPvarGetUbLocal(vars[i]);

      if( SCIPisFeasGT(scip, solval, ub) && EPSEQ(solval, ub, 10 * feastol) )
      {
         SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], ub) );
         SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
            SCIPvarGetName(vars[i]), solval, ub);
      }
      else if( SCIPisFeasLT(scip, solval, lb) && EPSEQ(solval, lb, 10 * feastol) )
      {
         SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], lb) );
         SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
            SCIPvarGetName(vars[i]), solval, lb);
      }
   }

   return SCIP_OKAY;
}
Example #10
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOneopt)
{  /*lint --e{715}*/

   SCIP_HEURDATA* heurdata;
   SCIP_SOL* bestsol;                        /* incumbent solution */
   SCIP_SOL* worksol;                        /* heuristic's working solution */
   SCIP_VAR** vars;                          /* SCIP variables                */
   SCIP_VAR** shiftcands;                    /* shiftable variables           */
   SCIP_ROW** lprows;                        /* SCIP LP rows                  */
   SCIP_Real* activities;                    /* row activities for working solution */
   SCIP_Real* shiftvals;

   SCIP_Real lb;
   SCIP_Real ub;
   SCIP_Bool localrows;
   SCIP_Bool valid;
   int nchgbound;
   int nbinvars;
   int nintvars;
   int nvars;
   int nlprows;
   int i;
   int nshiftcands;
   int shiftcandssize;
   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;

   /* we only want to process each solution once */
   bestsol = SCIPgetBestSol(scip);
   if( bestsol == NULL || heurdata->lastsolindex == SCIPsolGetIndex(bestsol) )
      return SCIP_OKAY;

   /* reset the timing mask to its default value (at the root node it could be different) */
   if( SCIPgetNNodes(scip) > 1 )
      SCIPheurSetTimingmask(heur, HEUR_TIMING);

   /* get problem variables */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
   nintvars += nbinvars;

   /* do not run if there are no discrete variables */
   if( nintvars == 0 )
   {
      *result = SCIP_DIDNOTRUN;
      return SCIP_OKAY;
   }

   if( heurtiming == SCIP_HEURTIMING_BEFOREPRESOL )
   {
      SCIP*                 subscip;            /* the subproblem created by zeroobj              */
      SCIP_HASHMAP*         varmapfw;           /* mapping of SCIP variables to sub-SCIP variables */
      SCIP_VAR**            subvars;            /* subproblem's variables                          */
      SCIP_Real* subsolvals;                    /* solution values of the subproblem               */

      SCIP_Real timelimit;                      /* time limit for zeroobj subproblem              */
      SCIP_Real memorylimit;                    /* memory limit for zeroobj subproblem            */

      SCIP_SOL* startsol;
      SCIP_SOL** subsols;
      int nsubsols;

      if( !heurdata->beforepresol )
         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;

      /* 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) );

      /* copy complete SCIP instance */
      valid = FALSE;
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "oneopt", TRUE, FALSE, TRUE, &valid) );
      SCIP_CALL( SCIPtransformProb(subscip) );

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

      /* copy the solution */
      SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
      SCIP_CALL( SCIPgetSolVals(scip, bestsol, nvars, vars, subsolvals) );

      /* create start solution for the subproblem */
      SCIP_CALL( SCIPcreateOrigSol(subscip, &startsol, NULL) );
      SCIP_CALL( SCIPsetSolVals(subscip, startsol, nvars, subvars, subsolvals) );

      /* try to add new solution to sub-SCIP and free it immediately */
      valid = FALSE;
      SCIP_CALL( SCIPtrySolFree(subscip, &startsol, FALSE, FALSE, FALSE, FALSE, &valid) );
      SCIPfreeBufferArray(scip, &subsolvals);
      SCIPhashmapFree(&varmapfw);

      /* disable statistic timing inside sub SCIP */
      SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );

      /* deactivate basically everything except oneopt in the sub-SCIP */
      SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
      SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
      SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
      SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
      SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

      /* if necessary, some of the parameters have to be unfixed first */
      if( SCIPisParamFixed(subscip, "lp/solvefreq") )
      {
         SCIPwarningMessage(scip, "unfixing parameter lp/solvefreq in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "lp/solvefreq") );
      }
      SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );

      if( SCIPisParamFixed(subscip, "heuristics/oneopt/freq") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/freq in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/freq") );
      }
      SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/oneopt/freq", 1) );

      if( SCIPisParamFixed(subscip, "heuristics/oneopt/forcelpconstruction") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/forcelpconstruction in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/forcelpconstruction") );
      }
      SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/forcelpconstruction", TRUE) );

      /* avoid recursive call, which would lead to an endless loop */
      if( SCIPisParamFixed(subscip, "heuristics/oneopt/beforepresol") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/beforepresol in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/beforepresol") );
      }
      SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/beforepresol", FALSE) );

      if( valid )
      {
         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 zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
         }

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

      /* 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);
      valid = FALSE;
      for( i = 0; i < nsubsols && !valid; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &valid) );
         if( valid )
            *result = SCIP_FOUNDSOL;
      }

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

      return SCIP_OKAY;
   }

   /* we can only work on solutions valid in the transformed space */
   if( SCIPsolIsOriginal(bestsol) )
      return SCIP_OKAY;

   if( heurtiming == SCIP_HEURTIMING_BEFORENODE && (SCIPhasCurrentNodeLP(scip) || heurdata->forcelpconstruction) )
   {
      SCIP_Bool cutoff;
      cutoff = FALSE;
      SCIP_CALL( SCIPconstructLP(scip, &cutoff) );
      SCIP_CALL( SCIPflushLP(scip) );

      /* get problem variables again, SCIPconstructLP() might have added new variables */
      SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
      nintvars += nbinvars;
   }

   /* we need an LP */
   if( SCIPgetNLPRows(scip) == 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   nchgbound = 0;

   /* initialize data */
   nshiftcands = 0;
   shiftcandssize = 8;
   heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
   SCIP_CALL( SCIPcreateSolCopy(scip, &worksol, bestsol) );
   SCIPsolSetHeur(worksol,heur);

   SCIPdebugMessage("Starting bound adjustment in 1-opt heuristic\n");

   /* maybe change solution values due to global bound changes first */
   for( i = nvars - 1; i >= 0; --i )
   {
      SCIP_VAR* var;
      SCIP_Real solval;

      var = vars[i];
      lb = SCIPvarGetLbGlobal(var);
      ub = SCIPvarGetUbGlobal(var);

      solval = SCIPgetSolVal(scip, bestsol,var);
      /* old solution value is smaller than the actual lower bound */
      if( SCIPisFeasLT(scip, solval, lb) )
      {
         /* set the solution value to the global lower bound */
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, lb) );
         ++nchgbound;
         SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to lb %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, lb);
      }
      /* old solution value is greater than the actual upper bound */
      else if( SCIPisFeasGT(scip, solval, SCIPvarGetUbGlobal(var)) )
      {
         /* set the solution value to the global upper bound */
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, ub) );
         ++nchgbound;
         SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to ub %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, ub);
      }
   }

   SCIPdebugMessage("number of bound changes (due to global bounds) = %d\n", nchgbound);
   SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );

   localrows = FALSE;
   valid = TRUE;

   /* initialize activities */
   for( i = 0; i < nlprows; ++i )
   {
      SCIP_ROW* row;

      row = lprows[i];
      assert(SCIProwGetLPPos(row) == i);

      if( !SCIProwIsLocal(row) )
      {
         activities[i] = SCIPgetRowSolActivity(scip, row, worksol);
         SCIPdebugMessage("Row <%s> has activity %g\n", SCIProwGetName(row), activities[i]);
         if( SCIPisFeasLT(scip, activities[i], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[i], SCIProwGetRhs(row)) )
         {
            valid = FALSE;
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
            SCIPdebugMessage("row <%s> activity %g violates bounds, lhs = %g, rhs = %g\n", SCIProwGetName(row), activities[i], SCIProwGetLhs(row), SCIProwGetRhs(row));
            break;
         }
      }
      else
         localrows = TRUE;
   }

   if( !valid )
   {
      /** @todo try to correct lp rows */
      SCIPdebugMessage("Some global bound changes were not valid in lp rows.\n");
      goto TERMINATE;
   }

   SCIP_CALL( SCIPallocBufferArray(scip, &shiftcands, shiftcandssize) );
   SCIP_CALL( SCIPallocBufferArray(scip, &shiftvals, shiftcandssize) );


   SCIPdebugMessage("Starting 1-opt heuristic\n");

   /* enumerate all integer variables and find out which of them are shiftable */
   for( i = 0; i < nintvars; i++ )
   {
      if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
      {
         SCIP_Real shiftval;
         SCIP_Real solval;

         /* find out whether the variable can be shifted */
         solval = SCIPgetSolVal(scip, worksol, vars[i]);
         shiftval = calcShiftVal(scip, vars[i], solval, activities);

         /* insert the variable into the list of shifting candidates */
         if( !SCIPisFeasZero(scip, shiftval) )
         {
            SCIPdebugMessage(" -> Variable <%s> can be shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);

            if( nshiftcands == shiftcandssize)
            {
               shiftcandssize *= 8;
               SCIP_CALL( SCIPreallocBufferArray(scip, &shiftcands, shiftcandssize) );
               SCIP_CALL( SCIPreallocBufferArray(scip, &shiftvals, shiftcandssize) );
            }
            shiftcands[nshiftcands] = vars[i];
            shiftvals[nshiftcands] = shiftval;
            nshiftcands++;
         }
      }
   }

   /* if at least one variable can be shifted, shift variables sorted by their objective */
   if( nshiftcands > 0 )
   {
      SCIP_Real shiftval;
      SCIP_Real solval;
      SCIP_VAR* var;

      /* the case that exactly one variable can be shifted is slightly easier */
      if( nshiftcands == 1 )
      {
         var = shiftcands[0];
         assert(var != NULL);
         solval = SCIPgetSolVal(scip, worksol, var);
         shiftval = shiftvals[0];
         assert(!SCIPisFeasZero(scip,shiftval));
         SCIPdebugMessage(" Only one shiftcand found, var <%s>, which is now shifted by<%1.1f> \n",
            SCIPvarGetName(var), shiftval);
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
      }
      else
      {
         SCIP_Real* objcoeffs;

         SCIP_CALL( SCIPallocBufferArray(scip, &objcoeffs, nshiftcands) );

         SCIPdebugMessage(" %d shiftcands found \n", nshiftcands);

         /* sort the variables by their objective, optionally weighted with the shiftval */
         if( heurdata->weightedobj )
         {
            for( i = 0; i < nshiftcands; ++i )
               objcoeffs[i] = SCIPvarGetObj(shiftcands[i])*shiftvals[i];
         }
         else
         {
            for( i = 0; i < nshiftcands; ++i )
               objcoeffs[i] = SCIPvarGetObj(shiftcands[i]);
         }

         /* sort arrays with respect to the first one */
         SCIPsortRealPtr(objcoeffs, (void**)shiftcands, nshiftcands);

         /* try to shift each variable -> Activities have to be updated */
         for( i = 0; i < nshiftcands; ++i )
         {
            var = shiftcands[i];
            assert(var != NULL);
            solval = SCIPgetSolVal(scip, worksol, var);
            shiftval = calcShiftVal(scip, var, solval, activities);
            SCIPdebugMessage(" -> Variable <%s> is now shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
            assert(i > 0 || !SCIPisFeasZero(scip, shiftval));
            assert(SCIPisFeasGE(scip, solval+shiftval, SCIPvarGetLbGlobal(var)) && SCIPisFeasLE(scip, solval+shiftval, SCIPvarGetUbGlobal(var)));
            SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
            SCIP_CALL( updateRowActivities(scip, activities, var, shiftval) );
         }

         SCIPfreeBufferArray(scip, &objcoeffs);
      }

      /* if the problem is a pure IP, try to install the solution, if it is a MIP, solve LP again to set the continuous
       * variables to the best possible value
       */
      if( nvars == nintvars || !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      {
         SCIP_Bool success;

         /* since we ignore local rows, we cannot guarantee their feasibility and have to set the checklprows flag to
          * TRUE if local rows are present
          */
         SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, localrows, &success) );

         if( success )
         {
            SCIPdebugMessage("found feasible shifted solution:\n");
            SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
            heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
            *result = SCIP_FOUNDSOL;
         }
      }
      else
      {
         SCIP_Bool lperror;
#ifdef NDEBUG
         SCIP_RETCODE retstat;
#endif

         SCIPdebugMessage("shifted solution should be feasible -> solve LP to fix continuous variables to best values\n");

         /* start diving to calculate the LP relaxation */
         SCIP_CALL( SCIPstartDive(scip) );

         /* set the bounds of the variables: fixed for integers, global bounds for continuous */
         for( i = 0; i < nvars; ++i )
         {
            if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
            {
               SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], SCIPvarGetLbGlobal(vars[i])) );
               SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], SCIPvarGetUbGlobal(vars[i])) );
            }
         }
         /* apply this after global bounds to not cause an error with intermediate empty domains */
         for( i = 0; i < nintvars; ++i )
         {
            if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
            {
               solval = SCIPgetSolVal(scip, worksol, vars[i]);
               SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], solval) );
               SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], solval) );
            }
         }

         /* solve LP */
         SCIPdebugMessage(" -> old LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));

         /**@todo in case of an MINLP, if SCIPisNLPConstructed() is TRUE, say, rather solve the NLP instead of the LP */
         /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
          * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
          */
#ifdef NDEBUG
         retstat = SCIPsolveDiveLP(scip, -1, &lperror, NULL);
         if( retstat != SCIP_OKAY )
         { 
            SCIPwarningMessage(scip, "Error while solving LP in Oneopt heuristic; LP solve terminated with code <%d>\n",retstat);
         }
#else
         SCIP_CALL( SCIPsolveDiveLP(scip, -1, &lperror, NULL) );
#endif

         SCIPdebugMessage(" -> new LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
         SCIPdebugMessage(" -> error=%u, status=%d\n", lperror, SCIPgetLPSolstat(scip));

         /* check if this is a feasible solution */
         if( !lperror && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
         {
            SCIP_Bool success;

            /* copy the current LP solution to the working solution */
            SCIP_CALL( SCIPlinkLPSol(scip, worksol) );
            SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, FALSE, &success) );

            /* check solution for feasibility */
            if( success )
            {
               SCIPdebugMessage("found feasible shifted solution:\n");
               SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
               heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
               *result = SCIP_FOUNDSOL;
            }
         }

         /* terminate the diving */
         SCIP_CALL( SCIPendDive(scip) );
      }
   }
   SCIPdebugMessage("Finished 1-opt heuristic\n");

   SCIPfreeBufferArray(scip, &shiftvals);
   SCIPfreeBufferArray(scip, &shiftcands);

 TERMINATE:
   SCIPfreeBufferArray(scip, &activities);
   SCIP_CALL( SCIPfreeSol(scip, &worksol) );

   return SCIP_OKAY;
}
/** creates the all variables of the subproblem */
static SCIP_RETCODE fixVariables(
   SCIP*                 scip,               /**< original SCIP data structure */
   SCIP*                 subscip,            /**< SCIP data structure for the subproblemd */
   SCIP_VAR**            subvars,            /**< the variables of the subproblem */
   int*                  selection,          /**< pool of solutions crossover will use */
   SCIP_HEURDATA*        heurdata,           /**< primal heuristic data */
   SCIP_Bool*            success             /**< pointer to store whether the problem was created successfully */
   )
{
   SCIP_VAR** vars;                          /* original scip variables                */
   SCIP_SOL** sols;                          /* pool of solutions                      */
   SCIP_Real fixingrate;                     /* percentage of variables that are fixed */

   int nvars;
   int nbinvars;
   int nintvars;

   int i;
   int j;
   int fixingcounter;

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

   /* get required data of the original problem */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );

   fixingcounter = 0;

   /* create the binary and general integer variables of the subproblem */
   for( i = 0; i < nbinvars + nintvars; i++ )
   {
      SCIP_Real solval;
      SCIP_Bool fixable;

      fixable = TRUE;
      solval = SCIPgetSolVal(scip, sols[selection[0]], vars[i]);

      /* check, whether variable's value is identical for each selected solution */
      for( j = 1; j < heurdata->nusedsols; j++ )
      {
         SCIP_Real varsolval;
         varsolval = SCIPgetSolVal(scip, sols[selection[j]], vars[i]);
         if( REALABS(solval - varsolval) > 0.5 )
         {
            fixable = FALSE;
            break;
         }
      }

      /* original solval can be outside transformed global bounds */
      fixable = fixable && SCIPvarGetLbGlobal(vars[i]) <= solval && solval <= SCIPvarGetUbGlobal(vars[i]);

      /* if solutions' values are equal, variable is fixed in the subproblem */
      if( fixable )
      {
         SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
         SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
         fixingcounter++;
      }
   }

   fixingrate = (SCIP_Real)fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));

   /* if all variables were fixed or amount of fixed variables is insufficient, skip residual part of
    * subproblem creation and abort immediately */
   *success = fixingcounter < nbinvars + nintvars && fixingrate >= heurdata->minfixingrate;

   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;
}
Example #13
0
/** arbitrary primal solution separation method of separator */
static
SCIP_DECL_SEPAEXECSOL(sepaExecsolImpliedbounds)
{  /*lint --e{715}*/
   SCIP_VAR** vars;
   SCIP_VAR** fracvars;
   SCIP_Real* solvals;
   SCIP_Real* fracvals;
   SCIP_Bool cutoff;
   int nvars;
   int nbinvars;
   int nfracs;
   int ncuts;
   int i;

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

   *result = SCIP_DIDNOTRUN;

   /* gets active problem variables */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
   if( nbinvars == 0 )
      return SCIP_OKAY;

   /* get solution values for all variables */
   SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
   SCIP_CALL( SCIPgetSolVals(scip, sol, nvars, vars, solvals) );

   /* get binary problem variables that are fractional in given solution */
   SCIP_CALL( SCIPallocBufferArray(scip, &fracvars, nbinvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &fracvals, nbinvars) );
   nfracs = 0;
   for( i = 0; i < nbinvars; ++i )
   {
      if( !SCIPisFeasIntegral(scip, solvals[i]) )
      {
         fracvars[nfracs] = vars[i];
         fracvals[nfracs] = solvals[i];
         nfracs++;
      }
   }

   /* call the cut separation */
   ncuts = 0;
   cutoff = FALSE;

   if( nfracs > 0 )
   {
      SCIP_CALL( separateCuts(scip, sepa, sol, solvals, fracvars, fracvals, nfracs, &cutoff, &ncuts) );
   }

   /* adjust result code */
   if ( cutoff )
      *result = SCIP_CUTOFF;
   else if ( ncuts > 0 )
      *result = SCIP_SEPARATED;
   else
      *result = SCIP_DIDNOTFIND;

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &fracvals);
   SCIPfreeBufferArray(scip, &fracvars);
   SCIPfreeBufferArray(scip, &solvals);

   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRootsoldiving) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_VAR** vars;
   SCIP_Real* rootsol;
   SCIP_Real* objchgvals;
   int* softroundings;
   int* intvalrounds;
   int nvars;
   int nbinvars;
   int nintvars;
   int nlpcands;
   SCIP_LPSOLSTAT lpsolstat;
   SCIP_Real absstartobjval;
   SCIP_Real objstep;
   SCIP_Real alpha;
   SCIP_Real oldobj;
   SCIP_Real newobj;
   SCIP_Bool lperror;
   SCIP_Bool lpsolchanged;
   SCIP_Longint nsolsfound;
   SCIP_Longint ncalls;
   SCIP_Longint nlpiterations;
   SCIP_Longint maxnlpiterations;
   int depth;
   int maxdepth;
   int maxdivedepth;
   int divedepth;
   int startnlpcands;
   int ncycles;
   int i;

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* don't dive two times at the same node */
   if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* only apply heuristic, if only a few solutions have been found */
   if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols )
      return SCIP_OKAY;

   /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
   depth = SCIPgetDepth(scip);
   maxdepth = SCIPgetMaxDepth(scip);
   maxdepth = MAX(maxdepth, 30);
   if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
      return SCIP_OKAY;

   /* calculate the maximal number of LP iterations until heuristic is aborted */
   nlpiterations = SCIPgetNNodeLPIterations(scip);
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
   maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
   maxnlpiterations += heurdata->maxlpiterofs;

   /* don't try to dive, if we took too many LP iterations during diving */
   if( heurdata->nlpiterations >= maxnlpiterations )
      return SCIP_OKAY;

   /* allow at least a certain number of LP iterations in this dive */
   maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);

   /* get number of fractional variables, that should be integral */
   nlpcands = SCIPgetNLPBranchCands(scip);

   /* don't try to dive, if there are no fractional variables */
   if( nlpcands == 0 )
      return SCIP_OKAY;

   /* calculate the maximal diving depth */
   nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
   if( SCIPgetNSolsFound(scip) == 0 )
      maxdivedepth = (int)(heurdata->depthfacnosol * nvars);
   else
      maxdivedepth = (int)(heurdata->depthfac * nvars);
   maxdivedepth = MAX(maxdivedepth, 10);

   *result = SCIP_DIDNOTFIND;

   /* get all variables of LP */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );

   /* get root solution value of all binary and integer variables */
   SCIP_CALL( SCIPallocBufferArray(scip, &rootsol, nbinvars + nintvars) );
   for( i = 0; i < nbinvars + nintvars; i++ )
      rootsol[i] = SCIPvarGetRootSol(vars[i]);

   /* get current LP objective value, and calculate length of a single step in an objective coefficient */
   absstartobjval = SCIPgetLPObjval(scip);
   absstartobjval = ABS(absstartobjval);
   absstartobjval = MAX(absstartobjval, 1.0);
   objstep = absstartobjval / 10.0;

   /* initialize array storing the preferred soft rounding directions and counting the integral value rounds */
   SCIP_CALL( SCIPallocBufferArray(scip, &softroundings, nbinvars + nintvars) );
   BMSclearMemoryArray(softroundings, nbinvars + nintvars);
   SCIP_CALL( SCIPallocBufferArray(scip, &intvalrounds, nbinvars + nintvars) );
   BMSclearMemoryArray(intvalrounds, nbinvars + nintvars);

   /* allocate temporary memory for buffering objective changes */
   SCIP_CALL( SCIPallocBufferArray(scip, &objchgvals, nbinvars + nintvars) );

   /* start diving */
   SCIP_CALL( SCIPstartDive(scip) );

   SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing rootsoldiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d, LPobj=%g, objstep=%g\n",
      SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth,
      SCIPgetLPObjval(scip), objstep);

   lperror = FALSE;
   divedepth = 0;
   lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
   alpha = heurdata->alpha;
   ncycles = 0;
   lpsolchanged = TRUE;
   startnlpcands = nlpcands;
   while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0 && ncycles < 10
      && (divedepth < 10
         || nlpcands <= startnlpcands - divedepth/2
         || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations))
      && !SCIPisStopped(scip) )
   {
      SCIP_Bool success;
      int hardroundingidx;
      int hardroundingdir;
      SCIP_Real hardroundingoldbd;
      SCIP_Real hardroundingnewbd;
      SCIP_Bool boundschanged;

      SCIP_RETCODE retcode;

      /* create solution from diving LP and try to round it */
      SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
      SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );

      if( success )
      {
         SCIPdebugMessage("rootsoldiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

         /* try to add solution to SCIP */
         SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

         /* check, if solution was feasible and good enough */
         if( success )
         {
            SCIPdebugMessage(" -> solution was feasible and good enough\n");
            *result = SCIP_FOUNDSOL;
         }
      }

      divedepth++;
      hardroundingidx = -1;
      hardroundingdir = 0;
      hardroundingoldbd = 0.0;
      hardroundingnewbd = 0.0;
      boundschanged = FALSE;

      SCIPdebugMessage("dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT":\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations);

      /* round solution x* from diving LP:
       *   - x~_j = down(x*_j)    if x*_j is integer or binary variable and x*_j <= root solution_j
       *   - x~_j = up(x*_j)      if x*_j is integer or binary variable and x*_j  > root solution_j
       *   - x~_j = x*_j          if x*_j is continuous variable
       * change objective function in diving LP:
       *   - if x*_j is integral, or j is a continuous variable, set obj'_j = alpha * obj_j
       *   - otherwise, set obj'_j = alpha * obj_j + sign(x*_j - x~_j)
       */
      for( i = 0; i < nbinvars + nintvars; i++ )
      {
         SCIP_VAR* var;
         SCIP_Real solval;

         var = vars[i];
         oldobj = SCIPgetVarObjDive(scip, var);
         newobj = oldobj;

         solval =  SCIPvarGetLPSol(var);
         if( SCIPisFeasIntegral(scip, solval) )
         {
            /* if the variable became integral after a soft rounding, count the rounds; after a while, fix it to its
             * current integral value;
             * otherwise, fade out the objective value
             */
            if( softroundings[i] != 0 && lpsolchanged )
            {
               intvalrounds[i]++;
               if( intvalrounds[i] == 5 && SCIPgetVarLbDive(scip, var) < SCIPgetVarUbDive(scip, var) - 0.5 )
               {
                  /* use exact integral value, if the variable is only integral within numerical tolerances */
                  solval = SCIPfloor(scip, solval+0.5);
                  SCIPdebugMessage(" -> fixing <%s> = %g\n", SCIPvarGetName(var), solval);
                  SCIP_CALL( SCIPchgVarLbDive(scip, var, solval) );
                  SCIP_CALL( SCIPchgVarUbDive(scip, var, solval) );
                  boundschanged = TRUE;
               }
            }
            else
               newobj = alpha * oldobj;
         }
         else if( solval <= rootsol[i] )
         {
            /* if the variable was soft rounded most of the time downwards, round it downwards by changing the bounds;
             * otherwise, apply soft rounding by changing the objective value
             */
            softroundings[i]--;
            if( softroundings[i] <= -10 && hardroundingidx == -1 )
            {
               SCIPdebugMessage(" -> hard rounding <%s>[%g] <= %g\n",
                  SCIPvarGetName(var), solval, SCIPfeasFloor(scip, solval));
               hardroundingidx = i;
               hardroundingdir = -1;
               hardroundingoldbd = SCIPgetVarUbDive(scip, var);
               hardroundingnewbd = SCIPfeasFloor(scip, solval);
               SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd) );
               boundschanged = TRUE;
            }
            else
               newobj = alpha * oldobj + objstep;
         }
         else
         {
            /* if the variable was soft rounded most of the time upwards, round it upwards by changing the bounds;
             * otherwise, apply soft rounding by changing the objective value
             */
            softroundings[i]++;
            if( softroundings[i] >= +10 && hardroundingidx == -1 )
            {
               SCIPdebugMessage(" -> hard rounding <%s>[%g] >= %g\n",
                  SCIPvarGetName(var), solval, SCIPfeasCeil(scip, solval));
               hardroundingidx = i;
               hardroundingdir = +1;
               hardroundingoldbd = SCIPgetVarLbDive(scip, var);
               hardroundingnewbd = SCIPfeasCeil(scip, solval);
               SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd) );
               boundschanged = TRUE;
            }
            else
               newobj = alpha * oldobj - objstep;
         }

         /* remember the objective change */
         objchgvals[i] = newobj;
      }

      /* apply objective changes if there was no bound change */
      if( !boundschanged )
      {
         /* apply cached changes on integer variables */
         for( i = 0; i < nbinvars + nintvars; ++i )
         {
            SCIP_VAR* var;

            var = vars[i];
            SCIPdebugMessage(" -> i=%d  var <%s>, solval=%g, rootsol=%g, oldobj=%g, newobj=%g\n",
               i, SCIPvarGetName(var), SCIPvarGetLPSol(var), rootsol[i], SCIPgetVarObjDive(scip, var), objchgvals[i]);

            SCIP_CALL( SCIPchgVarObjDive(scip, var, objchgvals[i]) );
         }

         /* fade out the objective values of the continuous variables */
         for( i = nbinvars + nintvars; i < nvars; i++ )
         {
            SCIP_VAR* var;

            var = vars[i];
            oldobj = SCIPgetVarObjDive(scip, var);
            newobj = alpha * oldobj;

            SCIPdebugMessage(" -> i=%d  var <%s>, solval=%g, oldobj=%g, newobj=%g\n",
               i, SCIPvarGetName(var), SCIPvarGetLPSol(var), oldobj, newobj);

            SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) );
         }
      }

   SOLVEAGAIN:
      /* resolve the diving LP */
      nlpiterations = SCIPgetNLPIterations(scip);

      retcode = SCIPsolveDiveLP(scip,  MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror);
      lpsolstat = SCIPgetLPSolstat(scip);

      /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
       * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      {
#ifndef NDEBUG
         if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY )
         {
            SCIP_CALL( retcode );
         }
#endif
         SCIPwarningMessage(scip, "Error while solving LP in Rootsoldiving heuristic; LP solve terminated with code <%d>\n", retcode);
         SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n");
      }

      if( lperror )
         break;

      /* update iteration count */
      heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;

      /* if no LP iterations were performed, we stayed at the same solution -> count this cycling */
      lpsolchanged = (SCIPgetNLPIterations(scip) != nlpiterations);
      if( lpsolchanged )
         ncycles = 0;
      else if( !boundschanged ) /* do not count if integral variables have been fixed */
         ncycles++;

      /* get LP solution status and number of fractional variables, that should be integral */
      if( lpsolstat == SCIP_LPSOLSTAT_INFEASIBLE && hardroundingidx != -1 )
      {
         SCIP_VAR* var;

         var = vars[hardroundingidx];

         /* round the hard rounded variable to the opposite direction and resolve the LP */
         if( hardroundingdir == -1 )
         {
            SCIPdebugMessage(" -> opposite hard rounding <%s> >= %g\n", SCIPvarGetName(var), hardroundingnewbd + 1.0);
            SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingoldbd) );
            SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd + 1.0) );
         }
         else
         {
            SCIPdebugMessage(" -> opposite hard rounding <%s> <= %g\n", SCIPvarGetName(var), hardroundingnewbd - 1.0);
            SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingoldbd) );
            SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd - 1.0) );
         }
         hardroundingidx = -1;
         goto SOLVEAGAIN;
      }
      if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
         nlpcands = SCIPgetNLPBranchCands(scip);
      SCIPdebugMessage("   -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands);
   }

   SCIPdebugMessage("---> diving finished: lpsolstat = %d, depth %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT"\n",
      lpsolstat, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations);

   /* check if a solution has been found */
   if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
   {
      SCIP_Bool success;

      /* create solution from diving LP */
      SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
      SCIPdebugMessage("rootsoldiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

      /* try to add solution to SCIP */
      SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

      /* check, if solution was feasible and good enough */
      if( success )
      {
         SCIPdebugMessage(" -> solution was feasible and good enough\n");
         *result = SCIP_FOUNDSOL;
      }
   }

   /* end diving */
   SCIP_CALL( SCIPendDive(scip) );

   if( *result == SCIP_FOUNDSOL )
      heurdata->nsuccess++;

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &objchgvals);
   SCIPfreeBufferArray(scip, &intvalrounds);
   SCIPfreeBufferArray(scip, &softroundings);
   SCIPfreeBufferArray(scip, &rootsol);

   SCIPdebugMessage("rootsoldiving heuristic finished\n");

   return SCIP_OKAY;
}
Example #15
0
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
   SCIP*                 scip,               /**< original SCIP data structure                                   */
   SCIP*                 subscip,            /**< SCIP data structure for the subproblem                         */
   SCIP_VAR**            subvars,            /**< the variables of the subproblem                                */
   SCIP_Real             minfixingrate,      /**< percentage of integer variables that have to be fixed          */
   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_Bool*            success             /**< pointer to store whether the problem was created successfully  */
   )
{
   SCIP_VAR** vars;                          /* original SCIP variables */

   SCIP_Real fixingrate;

   int nvars;
   int nbinvars;
   int nintvars;
   int i;
   int fixingcounter;

   assert(scip != NULL);
   assert(subscip != NULL);
   assert(subvars != NULL);

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

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

   fixingcounter = 0;

   /* change bounds of variables of the subproblem */
   for( i = 0; i < nbinvars + nintvars; i++ )
   {
      SCIP_Real lpsolval;
      SCIP_Real lb;
      SCIP_Real ub;

      /* get the current LP solution for each variable */
      lpsolval = SCIPgetRelaxSolVal(scip, vars[i]);

      if( SCIPisFeasIntegral(scip, lpsolval) )
      {
         /* fix variables to current LP solution if it is integral,
          * use exact integral value, if the variable is only integral within numerical tolerances
          */
         lb = SCIPfloor(scip, lpsolval+0.5);
         ub = lb;
         fixingcounter++;
      }
      else if( binarybounds )
      {
         /* if the sub problem should be a binary problem, change the bounds to nearest integers */
         lb = SCIPfeasFloor(scip,lpsolval);
         ub = SCIPfeasCeil(scip,lpsolval);
      }
      else
      {
         /* otherwise just copy bounds */
         lb =  SCIPvarGetLbGlobal(vars[i]);
         ub =  SCIPvarGetUbGlobal(vars[i]);
      }

      /* perform the bound change */
      SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], lb) );
      SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], ub) );
   }

   /* abort, if all integer variables were fixed (which should not happen for MIP) */
   if( fixingcounter == nbinvars + nintvars )
   {
      *success = FALSE;
      return SCIP_OKAY;
   }
   else
      fixingrate = fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
   SCIPdebugMessage("fixing rate: %g = %d of %d\n", fixingrate, fixingcounter, nbinvars + nintvars);

   /* abort, if the amount of fixed variables is insufficient */
   if( fixingrate < minfixingrate )
   {
      *success = FALSE;
      return SCIP_OKAY;
   }

   if( uselprows )
   {
      SCIP_ROW** rows;                          /* original scip rows                         */
      int nrows;

      /* get the rows and their number */
      SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );

      /* copy all rows to linear constraints */
      for( i = 0; i < nrows; i++ )
      {
         SCIP_CONS* cons;
         SCIP_VAR** consvars;
         SCIP_COL** cols;
         SCIP_Real constant;
         SCIP_Real lhs;
         SCIP_Real rhs;
         SCIP_Real* vals;
         int nnonz;
         int j;

         /* ignore rows that are only locally valid */
         if( SCIProwIsLocal(rows[i]) )
            continue;

         /* get the row's data */
         constant = SCIProwGetConstant(rows[i]);
         lhs = SCIProwGetLhs(rows[i]) - constant;
         rhs = SCIProwGetRhs(rows[i]) - constant;
         vals = SCIProwGetVals(rows[i]);
         nnonz = SCIProwGetNNonz(rows[i]);
         cols = SCIProwGetCols(rows[i]);

         assert( lhs <= rhs );

         /* allocate memory array to be filled with the corresponding subproblem variables */
         SCIP_CALL( SCIPallocBufferArray(subscip, &consvars, nnonz) );
         for( j = 0; j < nnonz; j++ )
            consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];

         /* create a new linear constraint and add it to the subproblem */
         SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
               TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
         SCIP_CALL( SCIPaddCons(subscip, cons) );
         SCIP_CALL( SCIPreleaseCons(subscip, &cons) );

         /* free temporary memory */
         SCIPfreeBufferArray(subscip, &consvars);
      }
   }

   *success = TRUE;
   return SCIP_OKAY;
}
Example #16
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecTrivial)
{  /*lint --e{715}*/
   SCIP_VAR** vars;
   SCIP_SOL* lbsol;                     /* solution where all variables are set to their lower bounds */
   SCIP_SOL* ubsol;                     /* solution where all variables are set to their upper bounds */
   SCIP_SOL* zerosol;                   /* solution where all variables are set to zero */
   SCIP_SOL* locksol;                   /* solution where all variables are set to the bound with the fewer locks */

   SCIP_Real large;

   int nvars;
   int nbinvars;
   int i;

   SCIP_Bool success;
   SCIP_Bool zerovalid;

   *result = SCIP_DIDNOTRUN;

   if( SCIPgetNRuns(scip) > 1 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;
   success = FALSE;

   /* initialize data structure */
   SCIP_CALL( SCIPcreateSol(scip, &lbsol, heur) );
   SCIP_CALL( SCIPcreateSol(scip, &ubsol, heur) );
   SCIP_CALL( SCIPcreateSol(scip, &zerosol, heur) );
   SCIP_CALL( SCIPcreateSol(scip, &locksol, heur) );

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

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

   /* if the problem is binary, we do not have to check the zero solution, since it is equal to the lower bound
    * solution */
   zerovalid = (nvars != nbinvars);
   assert(vars != NULL || nvars == 0);

   for( i = 0; i < nvars; i++ )
   {
      SCIP_Real lb;
      SCIP_Real ub;

      assert(vars != NULL); /* this assert is needed for flexelint */

      lb = SCIPvarGetLbLocal(vars[i]);
      ub = SCIPvarGetUbLocal(vars[i]);
      
      /* if problem is obviously infeasible due to empty domain, stop */
      if( SCIPisGT(scip, lb, ub) )
         goto TERMINATE;

      /* set bounds to sufficient large value */
      if( SCIPisInfinity(scip, -lb) )
         lb = MIN(-large, ub);
      if( SCIPisInfinity(scip, ub) )
      {
         SCIP_Real tmp;

         tmp = SCIPvarGetLbLocal(vars[i]);
         ub = MAX(tmp, large);
      }

      SCIP_CALL( SCIPsetSolVal(scip, lbsol, vars[i], lb) );
      SCIP_CALL( SCIPsetSolVal(scip, ubsol, vars[i], ub) );

      /* try the zero vector, if it is in the bounds region */
      if( zerovalid )
      {
         if( SCIPisLE(scip, lb, 0.0) && SCIPisLE(scip, 0.0, ub) )
         {
            SCIP_CALL( SCIPsetSolVal(scip, zerosol, vars[i], 0.0) );
         }
         else
            zerovalid = FALSE;
      }

      /* set variables to the bound with fewer locks, if tie choose an average value */
      if( SCIPvarGetNLocksDown(vars[i]) >  SCIPvarGetNLocksUp(vars[i]) )
      {
         SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], ub) );
      }
      else if( SCIPvarGetNLocksDown(vars[i]) <  SCIPvarGetNLocksUp(vars[i]) )
      {
         SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], lb) );
      }
      else
      {
         SCIP_Real solval;
         solval = (lb+ub)/2.0;

         /* if a tie occurs, roughly every third integer variable will be rounded up */
         if( SCIPvarGetType(vars[i]) != SCIP_VARTYPE_CONTINUOUS )
            solval = i % 3 == 0 ? SCIPceil(scip,solval) : SCIPfloor(scip,solval);

         assert(SCIPisFeasLE(scip,SCIPvarGetLbLocal(vars[i]),solval) && SCIPisFeasLE(scip,solval,SCIPvarGetUbLocal(vars[i])));

         SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], solval) );
      }
   }

   /* try lower bound solution */
   SCIPdebugMessage("try lower bound solution\n");
   SCIP_CALL( SCIPtrySol(scip, lbsol, FALSE, FALSE, TRUE, TRUE, &success) );

   if( success )
   {
      SCIPdebugMessage("found feasible lower bound solution:\n");
      SCIPdebug( SCIP_CALL( SCIPprintSol(scip, lbsol, NULL, FALSE) ) );

      *result = SCIP_FOUNDSOL;
   }

   /* try upper bound solution */
   SCIPdebugMessage("try upper bound solution\n");
   SCIP_CALL( SCIPtrySol(scip, ubsol, FALSE, FALSE, TRUE, TRUE, &success) );

   if( success )
   {
      SCIPdebugMessage("found feasible upper bound solution:\n");
      SCIPdebug( SCIP_CALL( SCIPprintSol(scip, ubsol, NULL, FALSE) ) );

      *result = SCIP_FOUNDSOL;
   }

   /* try zero solution */
   if( zerovalid )
   {
      SCIPdebugMessage("try zero solution\n");
      SCIP_CALL( SCIPtrySol(scip, zerosol, FALSE, FALSE, TRUE, TRUE, &success) );

      if( success )
      {
         SCIPdebugMessage("found feasible zero solution:\n");
         SCIPdebug( SCIP_CALL( SCIPprintSol(scip, zerosol, NULL, FALSE) ) );

         *result = SCIP_FOUNDSOL;
      }
   }

   /* try lock solution */
   SCIPdebugMessage("try lock solution\n");
   SCIP_CALL( SCIPtrySol(scip, locksol, FALSE, FALSE, TRUE, TRUE, &success) );

   if( success )
   {
      SCIPdebugMessage("found feasible lock solution:\n");
      SCIPdebug( SCIP_CALL( SCIPprintSol(scip, locksol, NULL, FALSE) ) );

      *result = SCIP_FOUNDSOL;
   }

TERMINATE:
   /* free solutions */
   SCIP_CALL( SCIPfreeSol(scip, &lbsol) );
   SCIP_CALL( SCIPfreeSol(scip, &ubsol) );
   SCIP_CALL( SCIPfreeSol(scip, &zerosol) );
   SCIP_CALL( SCIPfreeSol(scip, &locksol) );

   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;
}
Example #18
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 #19
0
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpStrongcg)
{  /*lint --e{715}*/
   SCIP_SEPADATA* sepadata;
   SCIP_VAR** vars;
   SCIP_COL** cols;
   SCIP_ROW** rows;
   SCIP_Real* varsolvals;
   SCIP_Real* binvrow;
   SCIP_Real* cutcoefs;
   SCIP_Real cutrhs;
   SCIP_Real cutact;
   SCIP_Real maxscale;
   SCIP_Longint maxdnom;
   int* basisind;
   int* inds;
   int ninds;
   int nvars;
   int ncols;
   int nrows;
   int ncalls;
   int depth;
   int maxdepth;
   int maxsepacuts;
   int ncuts;
   int c;
   int i;
   int cutrank;
   SCIP_Bool success;
   SCIP_Bool cutislocal;
   char normtype;

   assert(sepa != NULL);
   assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   depth = SCIPgetDepth(scip);
   ncalls = SCIPsepaGetNCallsAtNode(sepa);

   /* only call separator, if we are not close to terminating */
   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only call the strong CG cut separator a given number of times at each node */
   if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
      || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
      return SCIP_OKAY;

   /* only call separator, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call separator, if the LP solution is basic */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* only call separator, if there are fractional variables */
   if( SCIPgetNLPBranchCands(scip) == 0 )
      return SCIP_OKAY;

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

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
   if( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
   if( ncols >= 50*nrows )
      return SCIP_OKAY;
   if( ncols >= 5*nrows )
   {
      int ncutsfound;

      ncutsfound = SCIPgetNCutsFound(scip);
      if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
      {
         sepadata->lastncutsfound = ncutsfound;
         *result = SCIP_DELAYED;
         return SCIP_OKAY;
      }
   }
#endif

   /* get the type of norm to use for efficacy calculations */
   SCIP_CALL( SCIPgetCharParam(scip, "separating/efficacynorm", &normtype) );

   /* set the maximal denominator in rational representation of strong CG cut and the maximal scale factor to
    * scale resulting cut to integral values to avoid numerical instabilities
    */
   /**@todo find better but still stable strong CG cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
   maxdepth = SCIPgetMaxDepth(scip);
   if( depth == 0 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/4 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/2 )
   {
      maxdnom = 100;
      maxscale = 100.0;
   }
   else
   {
      maxdnom = 10;
      maxscale = 10.0;
   }

   *result = SCIP_DIDNOTFIND;

   /* allocate temporary memory */
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &inds, nrows) );
   varsolvals = NULL; /* allocate this later, if needed */

   /* get basis indices */
   SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );

   /* get the maximal number of cuts allowed in a separation round */
   if( depth == 0 )
      maxsepacuts = sepadata->maxsepacutsroot;
   else
      maxsepacuts = sepadata->maxsepacuts;

   SCIPdebugMessage("searching strong CG cuts: %d cols, %d rows, maxdnom=%" SCIP_LONGINT_FORMAT ", maxscale=%g, maxcuts=%d\n",
      ncols, nrows, maxdnom, maxscale, maxsepacuts);

   /* for all basic columns belonging to integer variables, try to generate a strong CG cut */
   ncuts = 0;
   for( i = 0; i < nrows && ncuts < maxsepacuts && !SCIPisStopped(scip) && *result != SCIP_CUTOFF; ++i )
   {
      SCIP_Bool tryrow;

      tryrow = FALSE;
      c = basisind[i];
      if( c >= 0 )
      {
         SCIP_VAR* var;

         assert(c < ncols);
         var = SCIPcolGetVar(cols[c]);
         if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
         {
            SCIP_Real primsol;

            primsol = SCIPcolGetPrimsol(cols[c]);
            assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/

            if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
            {
               SCIPdebugMessage("trying strong CG cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
               tryrow = TRUE;
            }
         }
      }
#ifdef SEPARATEROWS
      else
      {
         SCIP_ROW* row;

         assert(0 <= -c-1 && -c-1 < nrows);
         row = rows[-c-1];
         if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
         {
            SCIP_Real primsol;

            primsol = SCIPgetRowActivity(scip, row);
            if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
            {
               SCIPdebugMessage("trying strong CG cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
               tryrow = TRUE;
            }
         }
      }
#endif

      if( tryrow )
      {
         /* get the row of B^-1 for this basic integer variable with fractional solution value */
         SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow, inds, &ninds) );

#ifdef SCIP_DEBUG
         /* initialize variables, that might not have been initialized in SCIPcalcMIR if success == FALSE */
         cutact = 0.0;
         cutrhs = SCIPinfinity(scip);
#endif
         /* create a strong CG cut out of the weighted LP rows using the B^-1 row as weights */
         SCIP_CALL( SCIPcalcStrongCG(scip, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, MINFRAC, MAXFRAC,
               binvrow, inds, ninds, 1.0, cutcoefs, &cutrhs, &cutact, &success, &cutislocal, &cutrank) );
         assert(ALLOWLOCAL || !cutislocal);
         SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);

         /* if successful, convert dense cut into sparse row, and add the row as a cut */
         if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
         {
            SCIP_VAR** cutvars;
            SCIP_Real* cutvals;
            SCIP_Real cutnorm;
            int cutlen;

            /* if this is the first successful cut, get the LP solution for all COLUMN variables */
            if( varsolvals == NULL )
            {
               int v;

               SCIP_CALL( SCIPallocBufferArray(scip, &varsolvals, nvars) );
               for( v = 0; v < nvars; ++v )
               {
                  if( SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_COLUMN )
                     varsolvals[v] = SCIPvarGetLPSol(vars[v]);
               }
            }
            assert(varsolvals != NULL);

            /* get temporary memory for storing the cut as sparse row */
            SCIP_CALL( SCIPallocBufferArray(scip, &cutvars, nvars) );
            SCIP_CALL( SCIPallocBufferArray(scip, &cutvals, nvars) );

            /* store the cut as sparse row, calculate activity and norm of cut */
            SCIP_CALL( storeCutInArrays(scip, nvars, vars, cutcoefs, varsolvals, normtype,
                  cutvars, cutvals, &cutlen, &cutact, &cutnorm) );

            SCIPdebugMessage(" -> strong CG cut for <%s>: act=%f, rhs=%f, norm=%f, eff=%f, rank=%d\n",
               c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
               cutact, cutrhs, cutnorm, (cutact - cutrhs)/cutnorm, cutrank);

            if( SCIPisPositive(scip, cutnorm) && SCIPisEfficacious(scip, (cutact - cutrhs)/cutnorm) )
            {
               SCIP_ROW* cut;
               char cutname[SCIP_MAXSTRLEN];

               /* create the cut */
               if( c >= 0 )
                  (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_x%d", SCIPgetNLPs(scip), c);
               else
                  (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_s%d", SCIPgetNLPs(scip), -c-1);
               SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) );
               SCIP_CALL( SCIPaddVarsToRow(scip, cut, cutlen, cutvars, cutvals) );
               /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
               SCIProwChgRank(cut, cutrank);

               assert(success);
#ifdef MAKECUTINTEGRAL
               /* try to scale the cut to integral values */
               SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                     maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
#else
#ifdef MAKEINTCUTINTEGRAL
               /* try to scale the cut to integral values if there are no continuous variables
                *  -> leads to an integral slack variable that can later be used for other cuts
                */
               {
                  int k = 0;
                  while ( k < cutlen && SCIPvarIsIntegral(cutvars[k]) )
                     ++k;
                  if( k == cutlen )
                  {
                     SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                           maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
                  }
               }
#endif
#endif

#ifndef FORCECUTINTEGRAL
               success = TRUE;
#endif

               if( success )
               {
                  if( !SCIPisCutEfficacious(scip, NULL, cut) )
                  {
                     SCIPdebugMessage(" -> strong CG cut <%s> no longer efficacious: act=%f, rhs=%f, norm=%f, eff=%f\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut));
                     /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
                     success = FALSE;
                  }
                  else
                  {
                     SCIP_Bool infeasible;

                     SCIPdebugMessage(" -> found strong CG cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut),
                        SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
                        SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));
                     /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
                     SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE, &infeasible) );
                     if ( infeasible )
                        *result = SCIP_CUTOFF;
                     else
                     {
                        if( !cutislocal )
                        {
                           SCIP_CALL( SCIPaddPoolCut(scip, cut) );
                        }
                        *result = SCIP_SEPARATED;
                     }
                     ncuts++;
                  }
               }
               else
               {
                  SCIPdebugMessage(" -> strong CG cut <%s> couldn't be scaled to integral coefficients: act=%f, rhs=%f, norm=%f, eff=%f\n",
                     cutname, cutact, cutrhs, cutnorm, SCIPgetCutEfficacy(scip, NULL, cut));
               }

               /* release the row */
               SCIP_CALL( SCIPreleaseRow(scip, &cut) );
            }

            /* free temporary memory */
            SCIPfreeBufferArray(scip, &cutvals);
            SCIPfreeBufferArray(scip, &cutvars);
         }
      }
   }

   /* free temporary memory */
   SCIPfreeBufferArrayNull(scip, &varsolvals);
   SCIPfreeBufferArray(scip, &inds);
   SCIPfreeBufferArray(scip, &binvrow);
   SCIPfreeBufferArray(scip, &basisind);
   SCIPfreeBufferArray(scip, &cutcoefs);

   SCIPdebugMessage("end searching strong CG cuts: found %d cuts\n", ncuts);

   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   return SCIP_OKAY;
}
Example #20
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 #21
0
/** create the extra constraint of local branching and add it to subscip */
static
SCIP_RETCODE addLocalBranchingConstraint(
   SCIP*                 scip,               /**< SCIP data structure of the original problem   */
   SCIP*                 subscip,            /**< SCIP data structure of the subproblem         */
   SCIP_VAR**            subvars,            /**< variables of the subproblem                   */
   SCIP_HEURDATA*        heurdata            /**< heuristic's data structure                    */
   )
{
   SCIP_CONS* cons;                        /* local branching constraint to create */
   SCIP_VAR** consvars;
   SCIP_VAR** vars;
   SCIP_SOL* bestsol;

   int nbinvars;
   int i;
   SCIP_Real lhs;
   SCIP_Real rhs;
   SCIP_Real* consvals;
   char consname[SCIP_MAXSTRLEN];

   (void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "%s_localbranchcons", SCIPgetProbName(scip));

   /* get the data of the variables and the best solution */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, NULL, &nbinvars, NULL, NULL, NULL) );
   bestsol = SCIPgetBestSol(scip);
   assert( bestsol != NULL );

   /* memory allocation */
   SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nbinvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &consvals, nbinvars) );

   /* set initial left and right hand sides of local branching constraint */
   lhs = (SCIP_Real)heurdata->emptyneighborhoodsize + 1.0;
   rhs = (SCIP_Real)heurdata->curneighborhoodsize;

   /* create the distance (to incumbent) function of the binary variables */
   for( i = 0; i < nbinvars; i++ )
   {
      SCIP_Real solval;

      solval = SCIPgetSolVal(scip, bestsol, vars[i]);
      assert( SCIPisFeasIntegral(scip,solval) );

      /* is variable i  part of the binary support of bestsol? */
      if( SCIPisFeasEQ(scip,solval,1.0) )
      {
         consvals[i] = -1.0;
         rhs -= 1.0;
         lhs -= 1.0;
      }
      else
         consvals[i] = 1.0;
      consvars[i] = subvars[i];
      assert( SCIPvarGetType(consvars[i]) == SCIP_VARTYPE_BINARY );
   }

   /* creates localbranching constraint and adds it to subscip */
   SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, consname, nbinvars, consvars, consvals,
         lhs, rhs, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
   SCIP_CALL( SCIPaddCons(subscip, cons) );
   SCIP_CALL( SCIPreleaseCons(subscip, &cons) );

   /* free local memory */
   SCIPfreeBufferArray(scip, &consvals);
   SCIPfreeBufferArray(scip, &consvars);

   return SCIP_OKAY;
}
Example #22
0
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
   SCIP*                 scip,               /**< original SCIP data structure                                  */
   SCIP*                 subscip,            /**< SCIP data structure for the subproblem                        */
   SCIP_VAR**            subvars,            /**< the variables of the subproblem                               */
   SCIP_Real             minfixingrate,      /**< percentage of integer variables that have to be fixed         */
   unsigned int*         randseed,           /**< a seed value for the random number generator                  */
   SCIP_Bool             uselprows           /**< should subproblem be created out of the rows in the LP rows?   */
   )
{
   SCIP_VAR** vars;                          /* original scip variables                    */
   SCIP_SOL* sol;                            /* pool of solutions                          */
   SCIP_Bool* marked;                        /* array of markers, which variables to fixed */
   SCIP_Bool fixingmarker;                   /* which flag should label a fixed variable?  */

   int nvars;
   int nbinvars;
   int nintvars;
   int i;
   int j;
   int nmarkers;

   /* get required data of the original problem */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
   sol = SCIPgetBestSol(scip);
   assert(sol != NULL);


   SCIP_CALL( SCIPallocBufferArray(scip, &marked, nbinvars+nintvars) );

   if( minfixingrate > 0.5 )
   {
      nmarkers = nbinvars + nintvars - (int) SCIPfloor(scip, minfixingrate*(nbinvars+nintvars));
      fixingmarker = FALSE;
   }
   else
   {
      nmarkers = (int) SCIPceil(scip, minfixingrate*(nbinvars+nintvars));
      fixingmarker = TRUE;
   }
   assert( 0 <= nmarkers && nmarkers <=  SCIPceil(scip,(nbinvars+nintvars)/2.0 ) );

   j = 0;
   BMSclearMemoryArray(marked, nbinvars+nintvars);
   while( j < nmarkers )
   {
      do
      {
         i = SCIPgetRandomInt(0, nbinvars+nintvars-1, randseed);
      }
      while( marked[i] );
      marked[i] = TRUE;
      j++;
   }
   assert( j == nmarkers );

   /* change bounds of variables of the subproblem */
   for( i = 0; i < nbinvars + nintvars; i++ )
   {
      /* fix all randomly marked variables */
      if( marked[i] == fixingmarker )
      {
         SCIP_Real solval;
         SCIP_Real lb;
         SCIP_Real ub;

         solval = SCIPgetSolVal(scip, sol, vars[i]);
         lb = SCIPvarGetLbGlobal(subvars[i]);
         ub = SCIPvarGetUbGlobal(subvars[i]);
         assert(SCIPisLE(scip, lb, ub));
         
         /* due to dual reductions, it may happen that the solution value is not in
            the variable's domain anymore */
         if( SCIPisLT(scip, solval, lb) )
            solval = lb;
         else if( SCIPisGT(scip, solval, ub) )
            solval = ub;
         
         /* perform the bound change */
         if( !SCIPisInfinity(scip, solval) && !SCIPisInfinity(scip, -solval) )
         {
            SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
            SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
         }
      }
   }

   if( uselprows )
   {
      SCIP_ROW** rows;   /* original scip rows */
      int nrows;

      /* get the rows and their number */
      SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );

      /* copy all rows to linear constraints */
      for( i = 0; i < nrows; i++ )
      {
         SCIP_CONS* cons;
         SCIP_VAR** consvars;
         SCIP_COL** cols;
         SCIP_Real constant;
         SCIP_Real lhs;
         SCIP_Real rhs;
         SCIP_Real* vals;
         int nnonz;

         /* ignore rows that are only locally valid */
         if( SCIProwIsLocal(rows[i]) )
            continue;

         /* get the row's data */
         constant = SCIProwGetConstant(rows[i]);
         lhs = SCIProwGetLhs(rows[i]) - constant;
         rhs = SCIProwGetRhs(rows[i]) - constant;
         vals = SCIProwGetVals(rows[i]);
         nnonz = SCIProwGetNNonz(rows[i]);
         cols = SCIProwGetCols(rows[i]);

         assert( lhs <= rhs );

         /* allocate memory array to be filled with the corresponding subproblem variables */
         SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nnonz) );
         for( j = 0; j < nnonz; j++ )
            consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];

         /* create a new linear constraint and add it to the subproblem */
         SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
               TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
         SCIP_CALL( SCIPaddCons(subscip, cons) );
         SCIP_CALL( SCIPreleaseCons(subscip, &cons) );

         /* free temporary memory */
         SCIPfreeBufferArray(scip, &consvars);
      }
   }

   SCIPfreeBufferArray(scip, &marked);
   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOctane)
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_SOL* sol;
   SCIP_SOL** first_sols;     /* stores the first ffirst sols in order to check for common violation of a row */

   SCIP_VAR** vars;           /* the variables of the problem */
   SCIP_VAR** fracvars;       /* variables, that are fractional in current LP solution */
   SCIP_VAR** subspacevars;   /* the variables on which the search is performed. Either coinciding with vars or with the
                               * space of all fractional variables of the current LP solution */

   SCIP_Real p;               /* n/2 - <delta,x> ( for some facet delta ) */
   SCIP_Real q;               /* <delta,a> */

   SCIP_Real* rayorigin;      /* origin of the ray, vector x in paper */
   SCIP_Real* raydirection;   /* direction of the ray, vector a in paper */
   SCIP_Real* negquotient;    /* negated quotient of rayorigin and raydirection, vector v in paper */
   SCIP_Real* lambda;         /* stores the distance of the facets (s.b.) to the origin of the ray */

   SCIP_Bool usefracspace;    /* determines whether the search concentrates on fractional variables and fixes integer ones */
   SCIP_Bool cons_viol;       /* used for checking whether a linear constraint is violated by one of the possible solutions */
   SCIP_Bool success;
   SCIP_Bool* sign;           /* signature of the direction of the ray */
   SCIP_Bool** facets;        /* list of extended facets */

   int nvars;            /* number of variables  */
   int nbinvars;         /* number of 0-1-variables */
   int nfracvars;        /* number of fractional variables in current LP solution */
   int nsubspacevars;    /* dimension of the subspace on which the search is performed */
   int nfacets;          /* number of facets hidden by the ray that where already found */
   int i;                /* counter */
   int j;                /* counter */
   int f_max;            /* {0,1}-points to be checked */
   int f_first;          /* {0,1}-points to be generated at first in order to check whether a restart is necessary */
   int r;                /* counter */
   int firstrule;

   int* perm;            /* stores the way in which the coordinates were permuted */
   int* fracspace;       /* maps the variables of the subspace to the original variables */

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* OCTANE is for use in 0-1 programs only */
   if( nvars != nbinvars )
      return SCIP_OKAY;

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

   /* don't call heuristic, if it was not successful enough in the past */
   /*lint --e{647}*/
   if( SCIPgetNNodes(scip) % (SCIPheurGetNCalls(heur) / (100 * SCIPheurGetNBestSolsFound(heur) + 10*heurdata->nsuccess + 1) + 1) != 0 )
      return SCIP_OKAY;

   SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, NULL, NULL, &nfracvars, NULL) );

   /* don't use integral starting points */
   if( nfracvars == 0 )
      return SCIP_OKAY;

   /* get working pointers from heurdata */
   sol = heurdata->sol;
   assert( sol != NULL );
   f_max = heurdata->f_max;
   f_first = heurdata->f_first;
   usefracspace = heurdata->usefracspace;

   SCIP_CALL( SCIPallocBufferArray(scip, &fracspace, nvars) );

   /* determine the space one which OCTANE should work either as the whole space or as the space of fractional variables */
   if( usefracspace )
   {
      nsubspacevars = nfracvars;
      SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );
      BMScopyMemoryArray(subspacevars, fracvars, nsubspacevars);
      for( i = nvars - 1; i >= 0; --i )
         fracspace[i] = -1;
      for( i = nsubspacevars - 1; i >= 0; --i )
         fracspace[SCIPvarGetProbindex(subspacevars[i])] = i;
   }
   else
   {
      int currentindex;

      nsubspacevars = nvars;
      SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );

      /* only copy the variables which are in the current LP */
      currentindex = 0;
      for( i = 0; i < nvars; ++i )
      {
         if( SCIPcolGetLPPos(SCIPvarGetCol(vars[i])) >= 0 )
         {
            subspacevars[currentindex] = vars[i];
            fracspace[i] = currentindex;
            ++currentindex;

         }
         else
         {
            fracspace[i] = -1;
            --nsubspacevars;
         }
      }
   }

   /* nothing to do for empty search space */
   if( nsubspacevars == 0 )
      return SCIP_OKAY;

   assert(0 < nsubspacevars && nsubspacevars <= nvars);

   for( i = 0; i < nsubspacevars; i++)
      assert(fracspace[SCIPvarGetProbindex(subspacevars[i])] == i);

   /* at most 2^(n-1) facets can be hit */
   if( nsubspacevars < 30 )
   {
      /*lint --e{701}*/
      assert(f_max > 0);
      f_max = MIN(f_max, 1 << (nsubspacevars - 1) );
   }

   f_first = MIN(f_first, f_max);

   /* memory allocation */
   SCIP_CALL( SCIPallocBufferArray(scip, &rayorigin, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &raydirection, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &negquotient, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &sign, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &perm, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &lambda, f_max + 1) );
   SCIP_CALL( SCIPallocBufferArray(scip, &facets, f_max + 1) );
   for( i = f_max; i >= 0; --i )
   {
      /*lint --e{866}*/
      SCIP_CALL( SCIPallocBufferArray(scip, &facets[i], nsubspacevars) );
   }
   SCIP_CALL( SCIPallocBufferArray(scip, &first_sols, f_first) );

   *result = SCIP_DIDNOTFIND;

   /* starting OCTANE */
   SCIPdebugMessage("run Octane heuristic on %s variables, which are %d vars, generate at most %d facets, using rule number %d\n",
      usefracspace ? "fractional" : "all", nsubspacevars, f_max, (heurdata->lastrule+1)%5);

   /* generate starting point in original coordinates */
   SCIP_CALL( generateStartingPoint(scip, rayorigin, subspacevars, nsubspacevars) );
   for( i = nsubspacevars - 1; i >= 0; --i )
      rayorigin[i] -= 0.5;

   firstrule = heurdata->lastrule;
   ++firstrule;
   for( r = firstrule; r <= firstrule + 10 && !SCIPisStopped(scip); r++ )
   {
      SCIP_ROW** rows;
      int nrows;

      /* generate shooting ray in original coordinates by certain rules */
      switch(r % 5)
      {
      case 1:
         if( heurdata->useavgnbray )
         {
            SCIP_CALL( generateAverageNBRay(scip, raydirection, fracspace, subspacevars, nsubspacevars) );
         }
         break;
      case 2:
         if( heurdata->useobjray )
         {
            SCIP_CALL( generateObjectiveRay(scip, raydirection, subspacevars, nsubspacevars) );
         }
         break;
      case 3:
         if( heurdata->usediffray )
         {
            SCIP_CALL( generateDifferenceRay(scip, raydirection, subspacevars, nsubspacevars) );
         }
         break;
      case 4:
         if( heurdata->useavgwgtray && SCIPisLPSolBasic(scip) )
         {
            SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, TRUE) );
         }
         break;
      case 0:
         if( heurdata->useavgray && SCIPisLPSolBasic(scip) )
         {
            SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, FALSE) );
         }
         break;
      default:
         SCIPerrorMessage("invalid ray rule identifier\n");
         SCIPABORT();
      }

      /* there must be a feasible direction for the shooting ray */
      if( isZero(scip, raydirection, nsubspacevars) )
         continue;

      /* transform coordinates such that raydirection >= 0 */
      flipCoords(rayorigin, raydirection, sign, nsubspacevars);

      for( i = f_max - 1; i >= 0; --i)
         lambda[i] = SCIPinfinity(scip);

      /* calculate negquotient, initialize perm, facets[0], p, and q */
      p = 0.5 * nsubspacevars;
      q = 0.0;
      for( i = nsubspacevars - 1; i >= 0; --i )
      {
         /* calculate negquotient, the ratio of rayorigin and raydirection, paying special attention to the case raydirection[i] == 0 */
         if( SCIPisFeasZero(scip, raydirection[i]) )
         {
            if( rayorigin[i] < 0 )
               negquotient[i] = SCIPinfinity(scip);
            else
               negquotient[i] = -SCIPinfinity(scip);
         }
         else
            negquotient[i] = - (rayorigin[i] / raydirection[i]);

         perm[i] = i;

         /* initialization of facets[0] to the all-one facet with p and q its characteristic values */
         facets[0][i] = TRUE;
         p -= rayorigin[i];
         q += raydirection[i];
      }

      assert(SCIPisPositive(scip, q));

      /* resort the coordinates in nonincreasing order of negquotient */
      SCIPsortDownRealRealRealBoolPtr( negquotient, raydirection, rayorigin, sign, (void**) subspacevars, nsubspacevars);

#ifndef NDEBUG
      for( i = 0; i < nsubspacevars; i++ )
         assert( raydirection[i] >= 0 );
      for( i = 1; i < nsubspacevars; i++ )
         assert( negquotient[i - 1] >= negquotient[i] );
#endif
      /* finished initialization */

      /* find the first facet of the octahedron hit by a ray shot from rayorigin into direction raydirection */
      for( i = 0; i < nsubspacevars && negquotient[i] * q > p; ++i )
      {
         facets[0][i] = FALSE;
         p += 2 * rayorigin[i];
         q -= 2 * raydirection[i];
         assert(SCIPisPositive(scip, p));
         assert(SCIPisPositive(scip, q));
      }

      /* avoid dividing by values close to 0.0 */
      if( !SCIPisFeasPositive(scip, q) )
         continue;

      /* assert necessary for flexelint */
      assert(q > 0);
      lambda[0] = p / q;

      nfacets = 1;

      /* find the first facets hit by the ray */
      for( i = 0; i < nfacets && i < f_first; ++i)
         generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);

      /* construct the first ffirst possible solutions */
      for( i = 0; i < nfacets && i < f_first; ++i )
      {
         SCIP_CALL( SCIPcreateSol(scip, &first_sols[i], heur) );
         SCIP_CALL( getSolFromFacet(scip, facets[i], first_sols[i], sign, subspacevars, nsubspacevars) );
         assert( first_sols[i] != NULL );
      }

      /* try, whether there is a row violated by all of the first ffirst solutions */
      cons_viol = FALSE;
      SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
      for( i = nrows - 1; i >= 0; --i )
      {
         if( !SCIProwIsLocal(rows[i]) )
         {
            SCIP_COL** cols;
            SCIP_Real constant;
            SCIP_Real lhs;
            SCIP_Real rhs;
            SCIP_Real rowval;
            SCIP_Real* coeffs;
            int nnonzerovars;
            int k;

            /* get the row's data */
            constant = SCIProwGetConstant(rows[i]);
            lhs = SCIProwGetLhs(rows[i]);
            rhs = SCIProwGetRhs(rows[i]);
            coeffs = SCIProwGetVals(rows[i]);
            nnonzerovars = SCIProwGetNNonz(rows[i]);
            cols = SCIProwGetCols(rows[i]);
            rowval = constant;

            for( j = nnonzerovars - 1; j >= 0; --j )
               rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[0], SCIPcolGetVar(cols[j]));

            /* if the row's lhs is violated by the first sol, test, whether it is violated by the next ones, too */
            if( lhs > rowval )
            {
               cons_viol = TRUE;
               for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
               {
                  rowval = constant;
                  for( j = nnonzerovars - 1; j >= 0; --j )
                     rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
                  if( lhs <= rowval )
                  {
                     cons_viol = FALSE;
                     break;
                  }
               }
            }
            /* dito for the right hand side */
            else if( rhs < rowval )
            {
               cons_viol = TRUE;
               for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
               {
                  rowval = constant;
                  for( j = nnonzerovars - 1; j >= 0; --j )
                     rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
                  if( rhs >= rowval )
                  {
                     cons_viol = FALSE;
                     break;
                  }
               }
            }
            /* break as soon as one row is violated by all of the ffirst solutions */
            if( cons_viol )
               break;
         }
      }


      if( !cons_viol )
      {
         /* if there was no row violated by all solutions, try whether one or more of them are feasible */
         for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
         {
            assert(first_sols[i] != NULL);
            SCIP_CALL( SCIPtrySol(scip, first_sols[i], FALSE, TRUE, FALSE, TRUE, &success) );
            if( success )
               *result = SCIP_FOUNDSOL;
         }
         /* search for further facets and construct and try solutions out of facets fixed as closest ones */
         for( i = f_first; i < f_max; ++i)
         {
            if( i >= nfacets )
               break;
            generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);
            SCIP_CALL( getSolFromFacet(scip, facets[i], sol, sign, subspacevars, nsubspacevars) );
            SCIP_CALL( SCIPtrySol(scip, sol, FALSE, TRUE, FALSE, TRUE, &success) );
            if( success )
               *result = SCIP_FOUNDSOL;
         }
      }

      /* finished OCTANE */
      for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
      {
         SCIP_CALL( SCIPfreeSol(scip, &first_sols[i]) );
      }
   }
   heurdata->lastrule = r;

   if( *result == SCIP_FOUNDSOL )
      ++(heurdata->nsuccess);

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &first_sols);
   for( i = f_max; i >= 0; --i )
      SCIPfreeBufferArray(scip, &facets[i]);
   SCIPfreeBufferArray(scip, &facets);
   SCIPfreeBufferArray(scip, &lambda);
   SCIPfreeBufferArray(scip, &perm);
   SCIPfreeBufferArray(scip, &sign);
   SCIPfreeBufferArray(scip, &negquotient);
   SCIPfreeBufferArray(scip, &raydirection);
   SCIPfreeBufferArray(scip, &rayorigin);
   SCIPfreeBufferArray(scip, &subspacevars);
   SCIPfreeBufferArray(scip, &fracspace);

   return SCIP_OKAY;
}