/* glpios05.c (Gomory's mixed integer cut generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010, 2011 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpios.h" /*********************************************************************** * NAME * * ios_gmi_gen - generate Gomory's mixed integer cuts. * * SYNOPSIS * * #include "glpios.h" * void ios_gmi_gen(glp_tree *tree, IOSPOOL *pool); * * DESCRIPTION * * The routine ios_gmi_gen generates Gomory's mixed integer cuts for * the current point and adds them to the cut pool. */ #define MAXCUTS 50 /* maximal number of cuts to be generated for one round */ struct worka { /* Gomory's cut generator working area */ int *ind; /* int ind[1+n]; */ double *val; /* double val[1+n]; */ double *phi; /* double phi[1+m+n]; */ }; #define f(x) ((x) - floor(x)) /* compute fractional part of x */ static void gen_cut(glp_tree *tree, struct worka *worka, int j) { /* this routine tries to generate Gomory's mixed integer cut for specified structural variable x[m+j] of integer kind, which is basic and has fractional value in optimal solution to current LP relaxation */ glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; int *ind = worka->ind; double *val = worka->val; double *phi = worka->phi; int i, k, len, kind, stat; double lb, ub, alfa, beta, ksi, phi1, rhs; /* compute row of the simplex tableau, which (row) corresponds to specified basic variable xB[i] = x[m+j]; see (23) */ len = glp_eval_tab_row(mip, m+j, ind, val); /* determine beta[i], which a value of xB[i] in optimal solution to current LP relaxation; note that this value is the same as if it would be computed with formula (27); it is assumed that beta[i] is fractional enough */ beta = mip->col[j]->prim; /* compute cut coefficients phi and right-hand side rho, which correspond to formula (30); dense format is used, because rows of the simplex tableau is usually dense */ for (k = 1; k <= m+n; k++) phi[k] = 0.0; rhs = f(beta); /* initial value of rho; see (28), (32) */ for (j = 1; j <= len; j++) { /* determine original number of non-basic variable xN[j] */ k = ind[j]; xassert(1 <= k && k <= m+n); /* determine the kind, bounds and current status of xN[j] in optimal solution to LP relaxation */ if (k <= m) { /* auxiliary variable */ GLPROW *row = mip->row[k]; kind = GLP_CV; lb = row->lb; ub = row->ub; stat = row->stat; } else { /* structural variable */ GLPCOL *col = mip->col[k-m]; kind = col->kind; lb = col->lb; ub = col->ub; stat = col->stat; } /* xN[j] cannot be basic */ xassert(stat != GLP_BS); /* determine row coefficient ksi[i,j] at xN[j]; see (23) */ ksi = val[j]; /* if ksi[i,j] is too large in the magnitude, do not generate the cut */ if (fabs(ksi) > 1e+05) goto fini; /* if ksi[i,j] is too small in the magnitude, skip it */ if (fabs(ksi) < 1e-10) goto skip; /* compute row coefficient alfa[i,j] at y[j]; see (26) */ switch (stat) { case GLP_NF: /* xN[j] is free (unbounded) having non-zero ksi[i,j]; do not generate the cut */ goto fini; case GLP_NL: /* xN[j] has active lower bound */ alfa = - ksi; break; case GLP_NU: /* xN[j] has active upper bound */ alfa = + ksi; break; case GLP_NS: /* xN[j] is fixed; skip it */ goto skip; default: xassert(stat != stat); } /* compute cut coefficient phi'[j] at y[j]; see (21), (28) */ switch (kind) { case GLP_IV: /* y[j] is integer */ if (fabs(alfa - floor(alfa + 0.5)) < 1e-10) { /* alfa[i,j] is close to nearest integer; skip it */ goto skip; } else if (f(alfa) <= f(beta)) phi1 = f(alfa); else phi1 = (f(beta) / (1.0 - f(beta))) * (1.0 - f(alfa)); break; case GLP_CV: /* y[j] is continuous */ if (alfa >= 0.0) phi1 = + alfa; else phi1 = (f(beta) / (1.0 - f(beta))) * (- alfa); break; default: xassert(kind != kind); } /* compute cut coefficient phi[j] at xN[j] and update right- hand side rho; see (31), (32) */ switch (stat) { case GLP_NL: /* xN[j] has active lower bound */ phi[k] = + phi1; rhs += phi1 * lb; break; case GLP_NU: /* xN[j] has active upper bound */ phi[k] = - phi1; rhs -= phi1 * ub; break; default: xassert(stat != stat); } skip: ; } /* now the cut has the form sum_k phi[k] * x[k] >= rho, where cut coefficients are stored in the array phi in dense format; x[1,...,m] are auxiliary variables, x[m+1,...,m+n] are struc- tural variables; see (30) */ /* eliminate auxiliary variables in order to express the cut only through structural variables; see (33) */ for (i = 1; i <= m; i++) { GLPROW *row; GLPAIJ *aij; if (fabs(phi[i]) < 1e-10) continue; /* auxiliary variable x[i] has non-zero cut coefficient */ row = mip->row[i]; /* x[i] cannot be fixed */ xassert(row->type != GLP_FX); /* substitute x[i] = sum_j a[i,j] * x[m+j] */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) phi[m+aij->col->j] += phi[i] * aij->val; } /* convert the final cut to sparse format and substitute fixed (structural) variables */ len = 0; for (j = 1; j <= n; j++) { GLPCOL *col; if (fabs(phi[m+j]) < 1e-10) continue; /* structural variable x[m+j] has non-zero cut coefficient */ col = mip->col[j]; if (col->type == GLP_FX) { /* eliminate x[m+j] */ rhs -= phi[m+j] * col->lb; } else { len++; ind[len] = j; val[len] = phi[m+j]; } } if (fabs(rhs) < 1e-12) rhs = 0.0; /* if the cut inequality seems to be badly scaled, reject it to avoid numeric difficulties */ for (k = 1; k <= len; k++) { if (fabs(val[k]) < 1e-03) goto fini; if (fabs(val[k]) > 1e+03) goto fini; } /* add the cut to the cut pool for further consideration */ #if 0 ios_add_cut_row(tree, pool, GLP_RF_GMI, len, ind, val, GLP_LO, rhs); #else glp_ios_add_row(tree, NULL, GLP_RF_GMI, 0, len, ind, val, GLP_LO, rhs); #endif fini: return; } struct var { int j; double f; }; static int fcmp(const void *p1, const void *p2) { const struct var *v1 = p1, *v2 = p2; if (v1->f > v2->f) return -1; if (v1->f < v2->f) return +1; return 0; } void ios_gmi_gen(glp_tree *tree) { /* main routine to generate Gomory's cuts */ glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; struct var *var; int k, nv, j, size; struct worka _worka, *worka = &_worka; /* allocate working arrays */ var = xcalloc(1+n, sizeof(struct var)); worka->ind = xcalloc(1+n, sizeof(int)); worka->val = xcalloc(1+n, sizeof(double)); worka->phi = xcalloc(1+m+n, sizeof(double)); /* build the list of integer structural variables, which are basic and have fractional value in optimal solution to current LP relaxation */ nv = 0; for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; double frac; if (col->kind != GLP_IV) continue; if (col->type == GLP_FX) continue; if (col->stat != GLP_BS) continue; frac = f(col->prim); if (!(0.05 <= frac && frac <= 0.95)) continue; /* add variable to the list */ nv++, var[nv].j = j, var[nv].f = frac; } /* order the list by descending fractionality */ qsort(&var[1], nv, sizeof(struct var), fcmp); /* try to generate cuts by one for each variable in the list, but not more than MAXCUTS cuts */ size = glp_ios_pool_size(tree); for (k = 1; k <= nv; k++) { if (glp_ios_pool_size(tree) - size >= MAXCUTS) break; gen_cut(tree, worka, var[k].j); } /* free working arrays */ xfree(var); xfree(worka->ind); xfree(worka->val); xfree(worka->phi); return; } /* eof */