/** creates the rows of the subproblem */
static
SCIP_RETCODE createRows(
   SCIP*                 scip,               /**< original SCIP data structure */
   SCIP*                 subscip,            /**< SCIP data structure for the subproblem */
   SCIP_VAR**            subvars             /**< the variables of the subproblem */
   )
{
   SCIP_ROW** rows;                          /* original scip rows                       */
   SCIP_CONS* cons;                          /* new constraint                           */
   SCIP_VAR** consvars;                      /* new constraint's variables               */
   SCIP_COL** cols;                          /* original row's columns                   */

   SCIP_Real constant;                       /* constant added to the row                */
   SCIP_Real lhs;                            /* left hand side of the row                */
   SCIP_Real rhs;                            /* left right side of the row               */
   SCIP_Real* vals;                          /* variables' coefficient values of the row */

   int nrows;
   int nnonz;
   int i;
   int j;

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

   /* copy all rows to linear constraints */
   for( i = 0; i < nrows; i++ )
   {
      /* 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);
   }

   return SCIP_OKAY;
}
Example #2
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;
}
Example #3
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;
}
Example #4
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;
}
/** 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 #6
0
/** LP solution separation method for disjunctive cuts */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpDisjunctive)
{
   SCIP_SEPADATA* sepadata;
   SCIP_CONSHDLR* conshdlr;
   SCIP_DIGRAPH* conflictgraph;
   SCIP_ROW** rows;
   SCIP_COL** cols;
   SCIP_Real* cutcoefs = NULL;
   SCIP_Real* simplexcoefs1 = NULL;
   SCIP_Real* simplexcoefs2 = NULL;
   SCIP_Real* coef = NULL;
   SCIP_Real* binvrow = NULL;
   SCIP_Real* rowsmaxval = NULL;
   SCIP_Real* violationarray = NULL;
   int* fixings1 = NULL;
   int* fixings2 = NULL;
   int* basisind = NULL;
   int* basisrow = NULL;
   int* varrank = NULL;
   int* edgearray = NULL;
   int nedges;
   int ndisjcuts;
   int nrelevantedges;
   int nsos1vars;
   int nconss;
   int maxcuts;
   int ncalls;
   int depth;
   int ncols;
   int nrows;
   int ind;
   int j;
   int i;

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

   *result = SCIP_DIDNOTRUN;

   /* only generate disjunctive cuts if we are not close to terminating */
   if ( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only generate disjunctive cuts if an optimal LP solution is at hand */
   if ( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only generate disjunctive cuts if the LP solution is basic */
   if ( ! SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );

   /* return if LP has no columns or no rows */
   if ( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

   assert( cols != NULL );
   assert( rows != NULL );

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

   /* get constraint handler */
   conshdlr = sepadata->conshdlr;
   if ( conshdlr == NULL )
      return SCIP_OKAY;

   /* get number of constraints */
   nconss = SCIPconshdlrGetNConss(conshdlr);
   if ( nconss == 0 )
      return SCIP_OKAY;

   /* check for maxdepth < depth, maxinvcutsroot = 0 and maxinvcuts = 0 */
   depth = SCIPgetDepth(scip);
   if ( ( sepadata->maxdepth >= 0 && sepadata->maxdepth < depth )
      || ( depth == 0 && sepadata->maxinvcutsroot == 0 )
      || ( depth > 0 && sepadata->maxinvcuts == 0 ) )
      return SCIP_OKAY;

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

   /* get conflict graph and number of conflict graph edges (note that the digraph arcs were added in both directions) */
   conflictgraph = SCIPgetConflictgraphSOS1(conshdlr);
   nedges = (int)SCIPceil(scip, (SCIP_Real)SCIPdigraphGetNArcs(conflictgraph)/2);

   /* if too many conflict graph edges, the separator can be slow: delay it until no other cuts have been found */
   if ( sepadata->maxconfsdelay >= 0 && nedges >= sepadata->maxconfsdelay )
   {
      int ncutsfound;

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

   /* check basis status */
   for (j = 0; j < ncols; ++j)
   {
      if ( SCIPcolGetBasisStatus(cols[j]) == SCIP_BASESTAT_ZERO )
         return SCIP_OKAY;
   }

   /* get number of SOS1 variables */
   nsos1vars = SCIPgetNSOS1Vars(conshdlr);

   /* allocate buffer arrays */
   SCIP_CALL( SCIPallocBufferArray(scip, &edgearray, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &fixings1, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &fixings2, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violationarray, nedges) );

   /* get all violated conflicts {i, j} in the conflict graph and sort them based on the degree of a violation value */
   nrelevantedges = 0;
   for (j = 0; j < nsos1vars; ++j)
   {
      SCIP_VAR* var;

      var = SCIPnodeGetVarSOS1(conflictgraph, j);

      if ( SCIPvarIsActive(var) && ! SCIPisFeasZero(scip, SCIPcolGetPrimsol(SCIPvarGetCol(var))) && SCIPcolGetBasisStatus(SCIPvarGetCol(var)) == SCIP_BASESTAT_BASIC )
      {
         int* succ;
         int nsucc;

         /* get successors and number of successors */
         nsucc = SCIPdigraphGetNSuccessors(conflictgraph, j);
         succ = SCIPdigraphGetSuccessors(conflictgraph, j);

         for (i = 0; i < nsucc; ++i)
         {
            SCIP_VAR* varsucc;
            int succind;

            succind = succ[i];
            varsucc = SCIPnodeGetVarSOS1(conflictgraph, succind);
            if ( SCIPvarIsActive(varsucc) && succind < j && ! SCIPisFeasZero(scip, SCIPgetSolVal(scip, NULL, varsucc) ) &&
                 SCIPcolGetBasisStatus(SCIPvarGetCol(varsucc)) == SCIP_BASESTAT_BASIC )
            {
               fixings1[nrelevantedges] = j;
               fixings2[nrelevantedges] = succind;
               edgearray[nrelevantedges] = nrelevantedges;
               violationarray[nrelevantedges++] = SCIPgetSolVal(scip, NULL, var) * SCIPgetSolVal(scip, NULL, varsucc);
            }
         }
      }
   }

   /* sort violation score values */
   if ( nrelevantedges > 0)
      SCIPsortDownRealInt(violationarray, edgearray, nrelevantedges);
   else
   {
      SCIPfreeBufferArrayNull(scip, &violationarray);
      SCIPfreeBufferArrayNull(scip, &fixings2);
      SCIPfreeBufferArrayNull(scip, &fixings1);
      SCIPfreeBufferArrayNull(scip, &edgearray);

      return SCIP_OKAY;
   }
   SCIPfreeBufferArrayNull(scip, &violationarray);

   /* compute maximal number of cuts */
   if ( SCIPgetDepth(scip) == 0 )
      maxcuts = MIN(sepadata->maxinvcutsroot, nrelevantedges);
   else
      maxcuts = MIN(sepadata->maxinvcuts, nrelevantedges);
   assert( maxcuts > 0 );

   /* allocate buffer arrays */
   SCIP_CALL( SCIPallocBufferArray(scip, &varrank, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &rowsmaxval, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisrow, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &coef, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs1, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs2, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );

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

   /* create vector "basisrow" with basisrow[column of non-slack basis variable] = corresponding row of B^-1;
    * compute maximum absolute value of nonbasic row coefficients */
   for (j = 0; j < nrows; ++j)
   {
      SCIP_COL** rowcols;
      SCIP_Real* rowvals;
      SCIP_ROW* row;
      SCIP_Real val;
      SCIP_Real max = 0.0;
      int nnonz;

      /* fill basisrow vector */
      ind = basisind[j];
      if ( ind >= 0 )
         basisrow[ind] = j;

      /* compute maximum absolute value of nonbasic row coefficients */
      row = rows[j];
      assert( row != NULL );
      rowvals = SCIProwGetVals(row);
      nnonz = SCIProwGetNNonz(row);
      rowcols = SCIProwGetCols(row);

      for (i = 0; i < nnonz; ++i)
      {
         if ( SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_LOWER  || SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_UPPER )
         {
            val = REALABS(rowvals[i]);
            if ( SCIPisFeasGT(scip, val, max) )
               max = REALABS(val);
         }
      }

      /* handle slack variable coefficient and save maximum value */
      rowsmaxval[j] = MAX(max, 1.0);
   }

   /* initialize variable ranks with -1 */
   for (j = 0; j < ncols; ++j)
      varrank[j] = -1;

   /* free buffer array */
   SCIPfreeBufferArrayNull(scip, &basisind);

   /* for the most promising disjunctions: try to generate disjunctive cuts */
   ndisjcuts = 0;
   for (i = 0; i < maxcuts; ++i)
   {
      SCIP_Bool madeintegral;
      SCIP_Real cutlhs1;
      SCIP_Real cutlhs2;
      SCIP_Real bound1;
      SCIP_Real bound2;
      SCIP_ROW* row = NULL;
      SCIP_VAR* var;
      SCIP_COL* col;

      int nonbasicnumber;
      int cutrank = 0;
      int edgenumber;
      int rownnonz;

      edgenumber = edgearray[i];

      /* determine first simplex row */
      var = SCIPnodeGetVarSOS1(conflictgraph, fixings1[edgenumber]);
      col = SCIPvarGetCol(var);
      ind = SCIPcolGetLPPos(col);
      assert( ind >= 0 );
      assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );

      /* get the 'ind'th row of B^-1 and B^-1 \cdot A */
      SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
      SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );

      /* get the simplex-coefficients of the non-basic variables */
      SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs1, &nonbasicnumber) );

      /* get rank of variable if not known already */
      if ( varrank[ind] < 0 )
         varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
      cutrank = MAX(cutrank, varrank[ind]);

      /* get right hand side and bound of simplex talbeau row */
      cutlhs1 = SCIPcolGetPrimsol(col);
      if ( SCIPisFeasPositive(scip, cutlhs1) )
         bound1 = SCIPcolGetUb(col);
      else
         bound1 = SCIPcolGetLb(col);


      /* determine second simplex row */
      var = SCIPnodeGetVarSOS1(conflictgraph, fixings2[edgenumber]);
      col = SCIPvarGetCol(var);
      ind = SCIPcolGetLPPos(col);
      assert( ind >= 0 );
      assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );

      /* get the 'ind'th row of B^-1 and B^-1 \cdot A */
      SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
      SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );

      /* get the simplex-coefficients of the non-basic variables */
      SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs2, &nonbasicnumber) );

      /* get rank of variable if not known already */
      if ( varrank[ind] < 0 )
         varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
      cutrank = MAX(cutrank, varrank[ind]);

      /* get right hand side and bound of simplex talbeau row */
      cutlhs2 = SCIPcolGetPrimsol(col);
      if ( SCIPisFeasPositive(scip, cutlhs2) )
         bound2 = SCIPcolGetUb(col);
      else
         bound2 = SCIPcolGetLb(col);

      /* add coefficients to cut */
      SCIP_CALL( generateDisjCutSOS1(scip, sepa, rows, nrows, cols, ncols, ndisjcuts, TRUE, sepadata->strengthen, cutlhs1, cutlhs2, bound1, bound2, simplexcoefs1, simplexcoefs2, cutcoefs, &row, &madeintegral) );
      if ( row == NULL )
         continue;

      /* raise cutrank for present cut */
      ++cutrank;

      /* check if there are numerical evidences */
      if ( ( madeintegral && ( sepadata->maxrankintegral == -1 || cutrank <= sepadata->maxrankintegral ) )
         || ( ! madeintegral && ( sepadata->maxrank == -1 || cutrank <= sepadata->maxrank ) ) )
      {
         /* possibly add cut to LP if it is useful; in case the lhs of the cut is minus infinity (due to scaling) the cut is useless */
         rownnonz = SCIProwGetNNonz(row);
         if ( rownnonz > 0 && ! SCIPisInfinity(scip, -SCIProwGetLhs(row)) && ! SCIProwIsInLP(row) && SCIPisCutEfficacious(scip, NULL, row) )
         {
            SCIP_Bool infeasible;

            /* set cut rank */
            SCIProwChgRank(row, cutrank);

            /* add cut */
            SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
            if ( infeasible )
            {
               *result = SCIP_CUTOFF;
               break;
            }
            ++ndisjcuts;
         }
      }

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

   /* save total number of cuts found so far */
   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   /* evaluate the result of the separation */
   if ( *result != SCIP_CUTOFF )
   {
      if ( ndisjcuts > 0 )
         *result = SCIP_SEPARATED;
      else
         *result = SCIP_DIDNOTFIND;
   }

   SCIPdebugMessage("Number of found disjunctive cuts: %d.\n", ndisjcuts);

   /* free buffer arrays */
   SCIPfreeBufferArrayNull(scip, &cutcoefs);
   SCIPfreeBufferArrayNull(scip, &simplexcoefs2);
   SCIPfreeBufferArrayNull(scip, &simplexcoefs1);
   SCIPfreeBufferArrayNull(scip, &coef);
   SCIPfreeBufferArrayNull(scip, &binvrow);
   SCIPfreeBufferArrayNull(scip, &basisrow);
   SCIPfreeBufferArrayNull(scip, &fixings2);
   SCIPfreeBufferArrayNull(scip, &fixings1);
   SCIPfreeBufferArrayNull(scip, &edgearray);
   SCIPfreeBufferArrayNull(scip, &rowsmaxval);
   SCIPfreeBufferArrayNull(scip, &varrank);

   return SCIP_OKAY;
}
Example #7
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 #8
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/
{   /*lint --e{715}*/
    SCIP_HEURDATA* heurdata;
    SCIP_SOL* sol;
    SCIP_VAR** lpcands;
    SCIP_Real* lpcandssol;
    SCIP_ROW** lprows;
    SCIP_Real* activities;
    SCIP_ROW** violrows;
    SCIP_Real* nincreases;
    SCIP_Real* ndecreases;
    int* violrowpos;
    int* nfracsinrow;
    SCIP_Real increaseweight;
    SCIP_Real obj;
    SCIP_Real bestshiftval;
    SCIP_Real minobj;
    int nlpcands;
    int nlprows;
    int nvars;
    int nfrac;
    int nviolrows;
    int nprevviolrows;
    int minnviolrows;
    int nnonimprovingshifts;
    int c;
    int r;
    SCIP_Longint nlps;
    SCIP_Longint ncalls;
    SCIP_Longint nsolsfound;
    SCIP_Longint nnodes;

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

    *result = SCIP_DIDNOTRUN;

    /* 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 objective value is smaller than the cutoff bound */
    if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
        return SCIP_OKAY;

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

    /* don't call heuristic, if we have already processed the current LP solution */
    nlps = SCIPgetNLPs(scip);
    if( nlps == heurdata->lastlp )
        return SCIP_OKAY;
    heurdata->lastlp = nlps;

    /* don't call heuristic, if it was not successful enough in the past */
    ncalls = SCIPheurGetNCalls(heur);
    nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
    nnodes = SCIPgetNNodes(scip);
    if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 )
        return SCIP_OKAY;

    /* get fractional variables, that should be integral */
    /* todo check if heuristic should include implicit integer variables for its calculations */
    SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
    nfrac = nlpcands;

    /* only call heuristic, if LP solution is fractional */
    if( nfrac == 0 )
        return SCIP_OKAY;

    *result = SCIP_DIDNOTFIND;

    /* get LP rows */
    SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );

    SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);

    /* get memory for activities, violated rows, and row violation positions */
    nvars = SCIPgetNVars(scip);
    SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) );
    SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) );
    BMSclearMemoryArray(nfracsinrow, nlprows);
    BMSclearMemoryArray(nincreases, nvars);
    BMSclearMemoryArray(ndecreases, nvars);

    /* get the activities for all globally valid rows;
     * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
     */
    nviolrows = 0;
    for( r = 0; r < nlprows; ++r )
    {
        SCIP_ROW* row;

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

        if( !SCIProwIsLocal(row) )
        {
            activities[r] = SCIPgetRowActivity(scip, row);
            if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
                    || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
            {
                violrows[nviolrows] = row;
                violrowpos[r] = nviolrows;
                nviolrows++;
            }
            else
                violrowpos[r] = -1;
        }
    }

    /* calc the current number of fractional variables in rows */
    for( c = 0; c < nlpcands; ++c )
        addFracCounter(nfracsinrow, nlprows, lpcands[c], +1);

    /* get the working solution from heuristic's local data */
    sol = heurdata->sol;
    assert(sol != NULL);

    /* copy the current LP solution to the working solution */
    SCIP_CALL( SCIPlinkLPSol(scip, sol) );

    /* calculate the minimal objective value possible after rounding fractional variables */
    minobj = SCIPgetSolTransObj(scip, sol);
    assert(minobj < SCIPgetCutoffbound(scip));
    for( c = 0; c < nlpcands; ++c )
    {
        obj = SCIPvarGetObj(lpcands[c]);
        bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
        minobj += obj * (bestshiftval - lpcandssol[c]);
    }

    /* try to shift remaining variables in order to become/stay feasible */
    nnonimprovingshifts = 0;
    minnviolrows = INT_MAX;
    increaseweight = 1.0;
    while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS )
    {
        SCIP_VAR* shiftvar;
        SCIP_Real oldsolval;
        SCIP_Real newsolval;
        SCIP_Bool oldsolvalisfrac;
        int probindex;

        SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n",
                         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj),
                         SCIPretransformObj(scip, SCIPgetCutoffbound(scip)));

        nprevviolrows = nviolrows;

        /* choose next variable to process:
         *  - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows
         *  - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction
         */
        shiftvar = NULL;
        oldsolval = 0.0;
        newsolval = 0.0;
        if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) )
        {
            SCIP_ROW* row;
            int rowidx;
            int rowpos;
            int direction;

            rowidx = -1;
            rowpos = -1;
            row = NULL;
            if( nfrac > 0 )
            {
                for( rowidx = nviolrows-1; rowidx >= 0; --rowidx )
                {
                    row = violrows[rowidx];
                    rowpos = SCIProwGetLPPos(row);
                    assert(violrowpos[rowpos] == rowidx);
                    if( nfracsinrow[rowpos] > 0 )
                        break;
                }
            }
            if( rowidx == -1 )
            {
                rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed);
                row = violrows[rowidx];
                rowpos = SCIProwGetLPPos(row);
                assert(0 <= rowpos && rowpos < nlprows);
                assert(violrowpos[rowpos] == rowidx);
                assert(nfracsinrow[rowpos] == 0);
            }
            assert(violrowpos[rowpos] == rowidx);

            SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
                             SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );

            /* get direction in which activity must be shifted */
            assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row))
                   || SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
            direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1;

            /* search a variable that can shift the activity in the necessary direction */
            SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction,
                                      nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) );
        }

        if( shiftvar == NULL && nfrac > 0 )
        {
            SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n");
            SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) );
        }

        /* check, whether shifting was possible */
        if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) )
        {
            SCIPdebugMessage("shifting heuristic:  -> didn't find a shifting variable\n");
            break;
        }

        SCIPdebugMessage("shifting heuristic:  -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n",
                         SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar),
                         oldsolval, newsolval, SCIPvarGetObj(shiftvar));

        /* update row activities of globally valid rows */
        SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
                                    shiftvar, oldsolval, newsolval) );
        if( nviolrows >= nprevviolrows )
            nnonimprovingshifts++;
        else if( nviolrows < minnviolrows )
        {
            minnviolrows = nviolrows;
            nnonimprovingshifts = 0;
        }

        /* store new solution value and decrease fractionality counter */
        SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) );

        /* update fractionality counter and minimal objective value possible after shifting remaining variables */
        oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval)
                          && (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER);
        obj = SCIPvarGetObj(shiftvar);
        if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER)
                && oldsolvalisfrac )
        {
            assert(SCIPisFeasIntegral(scip, newsolval));
            nfrac--;
            nnonimprovingshifts = 0;
            minnviolrows = INT_MAX;
            addFracCounter(nfracsinrow, nlprows, shiftvar, -1);

            /* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */
            if( obj > 0.0 && newsolval > oldsolval )
                minobj += obj;
            else if( obj < 0.0 && newsolval < oldsolval )
                minobj -= obj;
        }
        else
        {
            /* update minimal possible objective value */
            minobj += obj * (newsolval - oldsolval);
        }

        /* update increase/decrease arrays */
        if( !oldsolvalisfrac )
        {
            probindex = SCIPvarGetProbindex(shiftvar);
            assert(0 <= probindex && probindex < nvars);
            increaseweight *= WEIGHTFACTOR;
            if( newsolval < oldsolval )
                ndecreases[probindex] += increaseweight;
            else
                nincreases[probindex] += increaseweight;
            if( increaseweight >= 1e+09 )
            {
                int i;

                for( i = 0; i < nvars; ++i )
                {
                    nincreases[i] /= increaseweight;
                    ndecreases[i] /= increaseweight;
                }
                increaseweight = 1.0;
            }
        }

        SCIPdebugMessage("shifting heuristic:  -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
                         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
    }

    /* check, if the new solution is feasible */
    if( nfrac == 0 && nviolrows == 0 )
    {
        SCIP_Bool stored;

        /* check solution for feasibility, and add it to solution store if possible
         * neither integrality nor feasibility of LP rows has to be checked, because this is already
         * done in the shifting heuristic itself; however, we better check feasibility of LP rows,
         * because of numerical problems with activity updating
         */
        SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );

        if( stored )
        {
            SCIPdebugMessage("found feasible shifted solution:\n");
            SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) );
            *result = SCIP_FOUNDSOL;
        }
    }

    /* free memory buffers */
    SCIPfreeBufferArray(scip, &ndecreases);
    SCIPfreeBufferArray(scip, &nincreases);
    SCIPfreeBufferArray(scip, &nfracsinrow);
    SCIPfreeBufferArray(scip, &violrowpos);
    SCIPfreeBufferArray(scip, &violrows);
    SCIPfreeBufferArray(scip, &activities);

    return SCIP_OKAY;
}
Example #9
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRounding) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_SOL* sol;
   SCIP_VAR** lpcands;
   SCIP_Real* lpcandssol;
   SCIP_ROW** lprows;
   SCIP_Real* activities;
   SCIP_ROW** violrows;
   int* violrowpos;
   SCIP_Real obj;
   SCIP_Real bestroundval;
   SCIP_Real minobj;
   int nlpcands;
   int nlprows;
   int nfrac;
   int nviolrows;
   int c;
   int r;
   SCIP_Longint nlps;
   SCIP_Longint ncalls;
   SCIP_Longint nsolsfound;
   SCIP_Longint nnodes;

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

   *result = SCIP_DIDNOTRUN;

   /* 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 objective value is smaller than the cutoff bound */
   if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
      return SCIP_OKAY;

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

   /* don't call heuristic, if we have already processed the current LP solution */
   nlps = SCIPgetNLPs(scip);
   if( nlps == heurdata->lastlp )
      return SCIP_OKAY;
   heurdata->lastlp = nlps;

   /* don't call heuristic, if it was not successful enough in the past */
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
   nnodes = SCIPgetNNodes(scip);
   if( nnodes % ((ncalls/heurdata->successfactor)/(nsolsfound+1)+1) != 0 )
      return SCIP_OKAY;

   /* get fractional variables, that should be integral */
   SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
   nfrac = nlpcands;

   /* only call heuristic, if LP solution is fractional */
   if( nfrac == 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   /* get LP rows */
   SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );

   SCIPdebugMessage("executing rounding heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);

   /* get memory for activities, violated rows, and row violation positions */
   SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );

   /* get the activities for all globally valid rows;
    * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
    */
   nviolrows = 0;
   for( r = 0; r < nlprows; ++r )
   {
      SCIP_ROW* row;

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

      if( !SCIProwIsLocal(row) )
      {
         activities[r] = SCIPgetRowActivity(scip, row);
         if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
            || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
         {
            violrows[nviolrows] = row;
            violrowpos[r] = nviolrows;
            nviolrows++;
         }
         else
            violrowpos[r] = -1;
      }
   }

   /* get the working solution from heuristic's local data */
   sol = heurdata->sol;
   assert(sol != NULL);

   /* copy the current LP solution to the working solution */
   SCIP_CALL( SCIPlinkLPSol(scip, sol) );

   /* calculate the minimal objective value possible after rounding fractional variables */
   minobj = SCIPgetSolTransObj(scip, sol);
   assert(minobj < SCIPgetCutoffbound(scip));
   for( c = 0; c < nlpcands; ++c )
   {
      obj = SCIPvarGetObj(lpcands[c]);
      bestroundval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
      minobj += obj * (bestroundval - lpcandssol[c]);
   }

   /* try to round remaining variables in order to become/stay feasible */
   while( nfrac > 0 )
   {
      SCIP_VAR* roundvar;
      SCIP_Real oldsolval;
      SCIP_Real newsolval;

      SCIPdebugMessage("rounding heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));

      /* minobj < SCIPgetCutoffbound(scip) should be true, otherwise the rounding variable selection
       * should have returned NULL. Due to possible cancellation we use SCIPisLE. */
      assert( SCIPisLE(scip, minobj, SCIPgetCutoffbound(scip)) );

      /* choose next variable to process:
       *  - if a violated row exists, round a variable decreasing the violation, that has least impact on other rows
       *  - otherwise, round a variable, that has strongest devastating impact on rows in opposite direction
       */
      if( nviolrows > 0 )
      {
         SCIP_ROW* row;
         int rowpos;

         row = violrows[nviolrows-1];
         rowpos = SCIProwGetLPPos(row);
         assert(0 <= rowpos && rowpos < nlprows);
         assert(violrowpos[rowpos] == nviolrows-1);

         SCIPdebugMessage("rounding heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
            SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
         if( SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) )
         {
            /* lhs is violated: select a variable rounding, that increases the activity */
            SCIP_CALL( selectIncreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
         }
         else
         {
            assert(SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
            /* rhs is violated: select a variable rounding, that decreases the activity */
            SCIP_CALL( selectDecreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
         }
      }
      else
      {
         SCIPdebugMessage("rounding heuristic: search rounding variable and try to stay feasible\n");
         SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &roundvar, &oldsolval, &newsolval) );
      }

      /* check, whether rounding was possible */
      if( roundvar == NULL )
      {
         SCIPdebugMessage("rounding heuristic:  -> didn't find a rounding variable\n");
         break;
      }

      SCIPdebugMessage("rounding heuristic:  -> round var <%s>, oldval=%g, newval=%g, obj=%g\n",
         SCIPvarGetName(roundvar), oldsolval, newsolval, SCIPvarGetObj(roundvar));

      /* update row activities of globally valid rows */
      SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows, 
            roundvar, oldsolval, newsolval) );

      /* store new solution value and decrease fractionality counter */
      SCIP_CALL( SCIPsetSolVal(scip, sol, roundvar, newsolval) );
      nfrac--;

      /* update minimal objective value possible after rounding remaining variables */
      obj = SCIPvarGetObj(roundvar);
      if( obj > 0.0 && newsolval > oldsolval )
         minobj += obj;
      else if( obj < 0.0 && newsolval < oldsolval )
         minobj -= obj;

      SCIPdebugMessage("rounding heuristic:  -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
   }

   /* check, if the new solution is feasible */
   if( nfrac == 0 && nviolrows == 0 )
   {
      SCIP_Bool stored;

      /* check solution for feasibility, and add it to solution store if possible
       * neither integrality nor feasibility of LP rows has to be checked, because this is already
       * done in the rounding heuristic itself; however, be better check feasibility of LP rows,
       * because of numerical problems with activity updating
       */
      SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );

      if( stored )
      {
#ifdef SCIP_DEBUG
         SCIPdebugMessage("found feasible rounded solution:\n");
         SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
         *result = SCIP_FOUNDSOL;
      }
   }

   /* free memory buffers */
   SCIPfreeBufferArray(scip, &violrowpos);
   SCIPfreeBufferArray(scip, &violrows);
   SCIPfreeBufferArray(scip, &activities);

   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;
}
/** generates the direction of the shooting ray as the average of the normalized non-basic vars and rows */
static
SCIP_RETCODE generateAverageNBRay(
   SCIP*                 scip,               /**< SCIP data structure                   */
   SCIP_Real*            raydirection,       /**< shooting ray                          */
   int*                  fracspace,          /**< index set of fractional variables     */
   SCIP_VAR**            subspacevars,       /**< pointer to fractional space variables */
   int                   nsubspacevars       /**< dimension of fractional space         */
   )
{
   SCIP_ROW** rows;
   SCIP_COL** cols;
   int nrows;
   int ncols;
   int i;

   assert(scip != NULL);
   assert(raydirection != NULL);
   assert(fracspace != NULL);
   assert(subspacevars != NULL);

   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );

   /* add up non-basic variables */
   for( i = nsubspacevars - 1; i >= 0; --i )
   {
      SCIP_Real solval;

      solval = SCIPvarGetLPSol(subspacevars[i]);

      if( SCIPisFeasEQ(scip, solval, SCIPvarGetLbLocal(subspacevars[i])) )
         raydirection[i] = +1.0;
      else if( SCIPisFeasEQ(scip, solval, SCIPvarGetUbLocal(subspacevars[i])) )
         raydirection[i] = -1.0;
      else
         raydirection[i] = 0.0;
   }

   /* add up non-basic rows */
   for( i = nrows - 1; i >= 0; --i )
   {
      SCIP_Real dualsol;
      SCIP_Real factor;
      SCIP_Real* coeffs;
      SCIP_Real rownorm;
      int j;
      int nnonz;

      dualsol = SCIProwGetDualsol(rows[i]);
      if( SCIPisFeasPositive(scip, dualsol) )
         factor = 1.0;
      else if( SCIPisFeasNegative(scip, dualsol) )
         factor = -1.0;
      else
         continue;

      /* get the row's data */
      coeffs = SCIProwGetVals(rows[i]);
      cols = SCIProwGetCols(rows[i]);

      nnonz = SCIProwGetNNonz(rows[i]);

      rownorm = 0.0;
      for( j = nnonz - 1; j >= 0; --j )
      {
         SCIP_VAR* var;
         var = SCIPcolGetVar(cols[j]);
         if( fracspace[SCIPvarGetProbindex(var)] >= 0 )
            rownorm += coeffs[j] * coeffs[j];
      }

      if( SCIPisFeasZero(scip,rownorm) )
         continue;
      else
      {
         assert(rownorm > 0);
         rownorm = SQRT(rownorm);
      }

      for( j = nnonz - 1; j >= 0; --j )
      {
         SCIP_VAR* var;
         int f;

         var = SCIPcolGetVar(cols[j]);
         f = fracspace[SCIPvarGetProbindex(var)];

         if( f >= 0 )
         {
            raydirection[f] += factor * coeffs[j] / rownorm;
            assert(SCIP_REAL_MIN <= raydirection[f] && raydirection[f]  <= SCIP_REAL_MAX);
         }
      }
   }
   return SCIP_OKAY;
}
/** generates the direction of the shooting ray as the average of the extreme rays of the basic cone */
static
SCIP_RETCODE generateAverageRay(
   SCIP*                 scip,               /**< SCIP data structure                   */
   SCIP_Real*            raydirection,       /**< shooting ray                          */
   SCIP_VAR**            subspacevars,       /**< pointer to fractional space variables */
   int                   nsubspacevars,      /**< dimension of fractional space         */
   SCIP_Bool             weighted            /**< should the rays be weighted?          */
   )
{
   SCIP_ROW** rows;
   SCIP_Real** tableaurows;
   SCIP_Real* rownorm;
   SCIP_Real rowweight;

   int nrows;
   int i;
   int j;

   assert(scip != NULL);
   assert(raydirection != NULL);
   assert(subspacevars != NULL);

   /* get data */
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );

   /* allocate memory */
   SCIP_CALL( SCIPallocBufferArray(scip, &tableaurows, nsubspacevars) );
   for( j = nsubspacevars - 1; j >= 0; --j )
   {
      /*lint --e{866}*/
      SCIP_CALL( SCIPallocBufferArray(scip, &tableaurows[j], nrows) );
   }

   SCIP_CALL( SCIPallocBufferArray(scip, &rownorm, nrows) );
   for( i = nrows - 1; i >= 0; --i )
      rownorm[i] = 0;

   /* get the relevant columns of the simplex tableau */
   for( j = nsubspacevars-1; j >= 0; --j )
   {
      assert(SCIPcolGetLPPos(SCIPvarGetCol(subspacevars[j])) >= 0);
      SCIP_CALL( SCIPgetLPBInvACol(scip, SCIPcolGetLPPos(SCIPvarGetCol(subspacevars[j])), tableaurows[j]) );
      for( i = nrows - 1; i >= 0; --i )
         rownorm[i] += tableaurows[j][i] * tableaurows[j][i];
   }

   /* take average over all rows of the tableau */
   for( i = nrows - 1; i >= 0; --i )
   {
      if( SCIPisFeasZero(scip, rownorm[i]) )
         continue;
      else
         rownorm[i] = SQRT(rownorm[i]);

      rowweight = 0.0;
      if( weighted )
      {
         rowweight = SCIProwGetDualsol(rows[i]);
         if( SCIPisFeasZero(scip, rowweight) )
            continue;
      }
      else
         rowweight = 1.0;

      for( j = nsubspacevars - 1; j >= 0; --j )
      {
         raydirection[j] += tableaurows[j][i] / (rownorm[i] * rowweight);
         assert(SCIP_REAL_MIN <= raydirection[j] && raydirection[j]  <= SCIP_REAL_MAX);
      }
   }

   /* free memory */
   SCIPfreeBufferArray(scip, &rownorm);
   for( j = nsubspacevars - 1; j >= 0; --j )
   {
      SCIPfreeBufferArray(scip, &tableaurows[j]);
   }
   SCIPfreeBufferArray(scip, &tableaurows);

   return SCIP_OKAY;
}