src/glpios05.c
author Alpar Juttner <alpar@cs.elte.hu>
Sun, 05 Dec 2010 17:35:23 +0100
changeset 2 4c8956a7bdf4
permissions -rw-r--r--
Set up CMAKE build environment
     1 /* glpios05.c (Gomory's mixed integer cut generator) */
     2 
     3 /***********************************************************************
     4 *  This code is part of GLPK (GNU Linear Programming Kit).
     5 *
     6 *  Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
     7 *  2009, 2010 Andrew Makhorin, Department for Applied Informatics,
     8 *  Moscow Aviation Institute, Moscow, Russia. All rights reserved.
     9 *  E-mail: <mao@gnu.org>.
    10 *
    11 *  GLPK is free software: you can redistribute it and/or modify it
    12 *  under the terms of the GNU General Public License as published by
    13 *  the Free Software Foundation, either version 3 of the License, or
    14 *  (at your option) any later version.
    15 *
    16 *  GLPK is distributed in the hope that it will be useful, but WITHOUT
    17 *  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
    18 *  or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
    19 *  License for more details.
    20 *
    21 *  You should have received a copy of the GNU General Public License
    22 *  along with GLPK. If not, see <http://www.gnu.org/licenses/>.
    23 ***********************************************************************/
    24 
    25 #include "glpios.h"
    26 
    27 /***********************************************************************
    28 *  NAME
    29 *
    30 *  ios_gmi_gen - generate Gomory's mixed integer cuts.
    31 *
    32 *  SYNOPSIS
    33 *
    34 *  #include "glpios.h"
    35 *  void ios_gmi_gen(glp_tree *tree, IOSPOOL *pool);
    36 *
    37 *  DESCRIPTION
    38 *
    39 *  The routine ios_gmi_gen generates Gomory's mixed integer cuts for
    40 *  the current point and adds them to the cut pool. */
    41 
    42 #define MAXCUTS 50
    43 /* maximal number of cuts to be generated for one round */
    44 
    45 struct worka
    46 {     /* Gomory's cut generator working area */
    47       int *ind; /* int ind[1+n]; */
    48       double *val; /* double val[1+n]; */
    49       double *phi; /* double phi[1+m+n]; */
    50 };
    51 
    52 #define f(x) ((x) - floor(x))
    53 /* compute fractional part of x */
    54 
    55 static void gen_cut(glp_tree *tree, struct worka *worka, int j)
    56 {     /* this routine tries to generate Gomory's mixed integer cut for
    57          specified structural variable x[m+j] of integer kind, which is
    58          basic and has fractional value in optimal solution to current
    59          LP relaxation */
    60       glp_prob *mip = tree->mip;
    61       int m = mip->m;
    62       int n = mip->n;
    63       int *ind = worka->ind;
    64       double *val = worka->val;
    65       double *phi = worka->phi;
    66       int i, k, len, kind, stat;
    67       double lb, ub, alfa, beta, ksi, phi1, rhs;
    68       /* compute row of the simplex tableau, which (row) corresponds
    69          to specified basic variable xB[i] = x[m+j]; see (23) */
    70       len = glp_eval_tab_row(mip, m+j, ind, val);
    71       /* determine beta[i], which a value of xB[i] in optimal solution
    72          to current LP relaxation; note that this value is the same as
    73          if it would be computed with formula (27); it is assumed that
    74          beta[i] is fractional enough */
    75       beta = mip->col[j]->prim;
    76       /* compute cut coefficients phi and right-hand side rho, which
    77          correspond to formula (30); dense format is used, because rows
    78          of the simplex tableau is usually dense */
    79       for (k = 1; k <= m+n; k++) phi[k] = 0.0;
    80       rhs = f(beta); /* initial value of rho; see (28), (32) */
    81       for (j = 1; j <= len; j++)
    82       {  /* determine original number of non-basic variable xN[j] */
    83          k = ind[j];
    84          xassert(1 <= k && k <= m+n);
    85          /* determine the kind, bounds and current status of xN[j] in
    86             optimal solution to LP relaxation */
    87          if (k <= m)
    88          {  /* auxiliary variable */
    89             GLPROW *row = mip->row[k];
    90             kind = GLP_CV;
    91             lb = row->lb;
    92             ub = row->ub;
    93             stat = row->stat;
    94          }
    95          else
    96          {  /* structural variable */
    97             GLPCOL *col = mip->col[k-m];
    98             kind = col->kind;
    99             lb = col->lb;
   100             ub = col->ub;
   101             stat = col->stat;
   102          }
   103          /* xN[j] cannot be basic */
   104          xassert(stat != GLP_BS);
   105          /* determine row coefficient ksi[i,j] at xN[j]; see (23) */
   106          ksi = val[j];
   107          /* if ksi[i,j] is too large in the magnitude, do not generate
   108             the cut */
   109          if (fabs(ksi) > 1e+05) goto fini;
   110          /* if ksi[i,j] is too small in the magnitude, skip it */
   111          if (fabs(ksi) < 1e-10) goto skip;
   112          /* compute row coefficient alfa[i,j] at y[j]; see (26) */
   113          switch (stat)
   114          {  case GLP_NF:
   115                /* xN[j] is free (unbounded) having non-zero ksi[i,j];
   116                   do not generate the cut */
   117                goto fini;
   118             case GLP_NL:
   119                /* xN[j] has active lower bound */
   120                alfa = - ksi;
   121                break;
   122             case GLP_NU:
   123                /* xN[j] has active upper bound */
   124                alfa = + ksi;
   125                break;
   126             case GLP_NS:
   127                /* xN[j] is fixed; skip it */
   128                goto skip;
   129             default:
   130                xassert(stat != stat);
   131          }
   132          /* compute cut coefficient phi'[j] at y[j]; see (21), (28) */
   133          switch (kind)
   134          {  case GLP_IV:
   135                /* y[j] is integer */
   136                if (fabs(alfa - floor(alfa + 0.5)) < 1e-10)
   137                {  /* alfa[i,j] is close to nearest integer; skip it */
   138                   goto skip;
   139                }
   140                else if (f(alfa) <= f(beta))
   141                   phi1 = f(alfa);
   142                else
   143                   phi1 = (f(beta) / (1.0 - f(beta))) * (1.0 - f(alfa));
   144                break;
   145             case GLP_CV:
   146                /* y[j] is continuous */
   147                if (alfa >= 0.0)
   148                   phi1 = + alfa;
   149                else
   150                   phi1 = (f(beta) / (1.0 - f(beta))) * (- alfa);
   151                break;
   152             default:
   153                xassert(kind != kind);
   154          }
   155          /* compute cut coefficient phi[j] at xN[j] and update right-
   156             hand side rho; see (31), (32) */
   157          switch (stat)
   158          {  case GLP_NL:
   159                /* xN[j] has active lower bound */
   160                phi[k] = + phi1;
   161                rhs += phi1 * lb;
   162                break;
   163             case GLP_NU:
   164                /* xN[j] has active upper bound */
   165                phi[k] = - phi1;
   166                rhs -= phi1 * ub;
   167                break;
   168             default:
   169                xassert(stat != stat);
   170          }
   171 skip:    ;
   172       }
   173       /* now the cut has the form sum_k phi[k] * x[k] >= rho, where cut
   174          coefficients are stored in the array phi in dense format;
   175          x[1,...,m] are auxiliary variables, x[m+1,...,m+n] are struc-
   176          tural variables; see (30) */
   177       /* eliminate auxiliary variables in order to express the cut only
   178          through structural variables; see (33) */
   179       for (i = 1; i <= m; i++)
   180       {  GLPROW *row;
   181          GLPAIJ *aij;
   182          if (fabs(phi[i]) < 1e-10) continue;
   183          /* auxiliary variable x[i] has non-zero cut coefficient */
   184          row = mip->row[i];
   185          /* x[i] cannot be fixed */
   186          xassert(row->type != GLP_FX);
   187          /* substitute x[i] = sum_j a[i,j] * x[m+j] */
   188          for (aij = row->ptr; aij != NULL; aij = aij->r_next)
   189             phi[m+aij->col->j] += phi[i] * aij->val;
   190       }
   191       /* convert the final cut to sparse format and substitute fixed
   192          (structural) variables */
   193       len = 0;
   194       for (j = 1; j <= n; j++)
   195       {  GLPCOL *col;
   196          if (fabs(phi[m+j]) < 1e-10) continue;
   197          /* structural variable x[m+j] has non-zero cut coefficient */
   198          col = mip->col[j];
   199          if (col->type == GLP_FX)
   200          {  /* eliminate x[m+j] */
   201             rhs -= phi[m+j] * col->lb;
   202          }
   203          else
   204          {  len++;
   205             ind[len] = j;
   206             val[len] = phi[m+j];
   207          }
   208       }
   209       if (fabs(rhs) < 1e-12) rhs = 0.0;
   210       /* if the cut inequality seems to be badly scaled, reject it to
   211          avoid numeric difficulties */
   212       for (k = 1; k <= len; k++)
   213       {  if (fabs(val[k]) < 1e-03) goto fini;
   214          if (fabs(val[k]) > 1e+03) goto fini;
   215       }
   216       /* add the cut to the cut pool for further consideration */
   217 #if 0
   218       ios_add_cut_row(tree, pool, GLP_RF_GMI, len, ind, val, GLP_LO,
   219          rhs);
   220 #else
   221       glp_ios_add_row(tree, NULL, GLP_RF_GMI, 0, len, ind, val, GLP_LO,
   222          rhs);
   223 #endif
   224 fini: return;
   225 }
   226 
   227 struct var { int j; double f; };
   228 
   229 static int fcmp(const void *p1, const void *p2)
   230 {     const struct var *v1 = p1, *v2 = p2;
   231       if (v1->f > v2->f) return -1;
   232       if (v1->f < v2->f) return +1;
   233       return 0;
   234 }
   235 
   236 void ios_gmi_gen(glp_tree *tree)
   237 {     /* main routine to generate Gomory's cuts */
   238       glp_prob *mip = tree->mip;
   239       int m = mip->m;
   240       int n = mip->n;
   241       struct var *var;
   242       int k, nv, j, size;
   243       struct worka _worka, *worka = &_worka;
   244       /* allocate working arrays */
   245       var = xcalloc(1+n, sizeof(struct var));
   246       worka->ind = xcalloc(1+n, sizeof(int));
   247       worka->val = xcalloc(1+n, sizeof(double));
   248       worka->phi = xcalloc(1+m+n, sizeof(double));
   249       /* build the list of integer structural variables, which are
   250          basic and have fractional value in optimal solution to current
   251          LP relaxation */
   252       nv = 0;
   253       for (j = 1; j <= n; j++)
   254       {  GLPCOL *col = mip->col[j];
   255          double frac;
   256          if (col->kind != GLP_IV) continue;
   257          if (col->type == GLP_FX) continue;
   258          if (col->stat != GLP_BS) continue;
   259          frac = f(col->prim);
   260          if (!(0.05 <= frac && frac <= 0.95)) continue;
   261          /* add variable to the list */
   262          nv++, var[nv].j = j, var[nv].f = frac;
   263       }
   264       /* order the list by descending fractionality */
   265       qsort(&var[1], nv, sizeof(struct var), fcmp);
   266       /* try to generate cuts by one for each variable in the list, but
   267          not more than MAXCUTS cuts */
   268       size = glp_ios_pool_size(tree);
   269       for (k = 1; k <= nv; k++)
   270       {  if (glp_ios_pool_size(tree) - size >= MAXCUTS) break;
   271          gen_cut(tree, worka, var[k].j);
   272       }
   273       /* free working arrays */
   274       xfree(var);
   275       xfree(worka->ind);
   276       xfree(worka->val);
   277       xfree(worka->phi);
   278       return;
   279 }
   280 
   281 /* eof */