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Diffstat (limited to 'test/monniaux/glpk-4.65/src/intopt/fpump.c')
| -rw-r--r-- | test/monniaux/glpk-4.65/src/intopt/fpump.c | 360 |
1 files changed, 360 insertions, 0 deletions
diff --git a/test/monniaux/glpk-4.65/src/intopt/fpump.c b/test/monniaux/glpk-4.65/src/intopt/fpump.c new file mode 100644 index 00000000..0bdd6d4e --- /dev/null +++ b/test/monniaux/glpk-4.65/src/intopt/fpump.c @@ -0,0 +1,360 @@ +/* fpump.c (feasibility pump heuristic) */ + +/*********************************************************************** +* This code is part of GLPK (GNU Linear Programming Kit). +* +* Copyright (C) 2009-2018 Andrew Makhorin, Department for Applied +* Informatics, Moscow Aviation Institute, Moscow, Russia. All rights +* reserved. E-mail: <mao@gnu.org>. +* +* 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 <http://www.gnu.org/licenses/>. +***********************************************************************/ + +#include "env.h" +#include "ios.h" +#include "rng.h" + +/*********************************************************************** +* NAME +* +* ios_feas_pump - feasibility pump heuristic +* +* SYNOPSIS +* +* #include "glpios.h" +* void ios_feas_pump(glp_tree *T); +* +* DESCRIPTION +* +* The routine ios_feas_pump is a simple implementation of the Feasi- +* bility Pump heuristic. +* +* REFERENCES +* +* M.Fischetti, F.Glover, and A.Lodi. "The feasibility pump." Math. +* Program., Ser. A 104, pp. 91-104 (2005). */ + +struct VAR +{ /* binary variable */ + int j; + /* ordinal number */ + int x; + /* value in the rounded solution (0 or 1) */ + double d; + /* sorting key */ +}; + +static int CDECL fcmp(const void *x, const void *y) +{ /* comparison routine */ + const struct VAR *vx = x, *vy = y; + if (vx->d > vy->d) + return -1; + else if (vx->d < vy->d) + return +1; + else + return 0; +} + +void ios_feas_pump(glp_tree *T) +{ glp_prob *P = T->mip; + int n = P->n; + glp_prob *lp = NULL; + struct VAR *var = NULL; + RNG *rand = NULL; + GLPCOL *col; + glp_smcp parm; + int j, k, new_x, nfail, npass, nv, ret, stalling; + double dist, tol; + xassert(glp_get_status(P) == GLP_OPT); + /* this heuristic is applied only once on the root level */ + if (!(T->curr->level == 0 && T->curr->solved == 1)) goto done; + /* determine number of binary variables */ + nv = 0; + for (j = 1; j <= n; j++) + { col = P->col[j]; + /* if x[j] is continuous, skip it */ + if (col->kind == GLP_CV) continue; + /* if x[j] is fixed, skip it */ + if (col->type == GLP_FX) continue; + /* x[j] is non-fixed integer */ + xassert(col->kind == GLP_IV); + if (col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0) + { /* x[j] is binary */ + nv++; + } + else + { /* x[j] is general integer */ + if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("FPUMP heuristic cannot be applied due to genera" + "l integer variables\n"); + goto done; + } + } + /* there must be at least one binary variable */ + if (nv == 0) goto done; + if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("Applying FPUMP heuristic...\n"); + /* build the list of binary variables */ + var = xcalloc(1+nv, sizeof(struct VAR)); + k = 0; + for (j = 1; j <= n; j++) + { col = P->col[j]; + if (col->kind == GLP_IV && col->type == GLP_DB) + var[++k].j = j; + } + xassert(k == nv); + /* create working problem object */ + lp = glp_create_prob(); +more: /* copy the original problem object to keep it intact */ + glp_copy_prob(lp, P, GLP_OFF); + /* we are interested to find an integer feasible solution, which + is better than the best known one */ + if (P->mip_stat == GLP_FEAS) + { int *ind; + double *val, bnd; + /* add a row and make it identical to the objective row */ + glp_add_rows(lp, 1); + ind = xcalloc(1+n, sizeof(int)); + val = xcalloc(1+n, sizeof(double)); + for (j = 1; j <= n; j++) + { ind[j] = j; + val[j] = P->col[j]->coef; + } + glp_set_mat_row(lp, lp->m, n, ind, val); + xfree(ind); + xfree(val); + /* introduce upper (minimization) or lower (maximization) + bound to the original objective function; note that this + additional constraint is not violated at the optimal point + to LP relaxation */ +#if 0 /* modified by xypron <xypron.glpk@gmx.de> */ + if (P->dir == GLP_MIN) + { bnd = P->mip_obj - 0.10 * (1.0 + fabs(P->mip_obj)); + if (bnd < P->obj_val) bnd = P->obj_val; + glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0); + } + else if (P->dir == GLP_MAX) + { bnd = P->mip_obj + 0.10 * (1.0 + fabs(P->mip_obj)); + if (bnd > P->obj_val) bnd = P->obj_val; + glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0); + } + else + xassert(P != P); +#else + bnd = 0.1 * P->obj_val + 0.9 * P->mip_obj; + /* xprintf("bnd = %f\n", bnd); */ + if (P->dir == GLP_MIN) + glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0); + else if (P->dir == GLP_MAX) + glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0); + else + xassert(P != P); +#endif + } + /* reset pass count */ + npass = 0; + /* invalidate the rounded point */ + for (k = 1; k <= nv; k++) + var[k].x = -1; +pass: /* next pass starts here */ + npass++; + if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("Pass %d\n", npass); + /* initialize minimal distance between the basic point and the + rounded one obtained during this pass */ + dist = DBL_MAX; + /* reset failure count (the number of succeeded iterations failed + to improve the distance) */ + nfail = 0; + /* if it is not the first pass, perturb the last rounded point + rather than construct it from the basic solution */ + if (npass > 1) + { double rho, temp; + if (rand == NULL) + rand = rng_create_rand(); + for (k = 1; k <= nv; k++) + { j = var[k].j; + col = lp->col[j]; + rho = rng_uniform(rand, -0.3, 0.7); + if (rho < 0.0) rho = 0.0; + temp = fabs((double)var[k].x - col->prim); + if (temp + rho > 0.5) var[k].x = 1 - var[k].x; + } + goto skip; + } +loop: /* innermost loop begins here */ + /* round basic solution (which is assumed primal feasible) */ + stalling = 1; + for (k = 1; k <= nv; k++) + { col = lp->col[var[k].j]; + if (col->prim < 0.5) + { /* rounded value is 0 */ + new_x = 0; + } + else + { /* rounded value is 1 */ + new_x = 1; + } + if (var[k].x != new_x) + { stalling = 0; + var[k].x = new_x; + } + } + /* if the rounded point has not changed (stalling), choose and + flip some its entries heuristically */ + if (stalling) + { /* compute d[j] = |x[j] - round(x[j])| */ + for (k = 1; k <= nv; k++) + { col = lp->col[var[k].j]; + var[k].d = fabs(col->prim - (double)var[k].x); + } + /* sort the list of binary variables by descending d[j] */ + qsort(&var[1], nv, sizeof(struct VAR), fcmp); + /* choose and flip some rounded components */ + for (k = 1; k <= nv; k++) + { if (k >= 5 && var[k].d < 0.35 || k >= 10) break; + var[k].x = 1 - var[k].x; + } + } +skip: /* check if the time limit has been exhausted */ + if (T->parm->tm_lim < INT_MAX && + (double)(T->parm->tm_lim - 1) <= + 1000.0 * xdifftime(xtime(), T->tm_beg)) goto done; + /* build the objective, which is the distance between the current + (basic) point and the rounded one */ + lp->dir = GLP_MIN; + lp->c0 = 0.0; + for (j = 1; j <= n; j++) + lp->col[j]->coef = 0.0; + for (k = 1; k <= nv; k++) + { j = var[k].j; + if (var[k].x == 0) + lp->col[j]->coef = +1.0; + else + { lp->col[j]->coef = -1.0; + lp->c0 += 1.0; + } + } + /* minimize the distance with the simplex method */ + glp_init_smcp(&parm); + if (T->parm->msg_lev <= GLP_MSG_ERR) + parm.msg_lev = T->parm->msg_lev; + else if (T->parm->msg_lev <= GLP_MSG_ALL) + { parm.msg_lev = GLP_MSG_ON; + parm.out_dly = 10000; + } + ret = glp_simplex(lp, &parm); + if (ret != 0) + { if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("Warning: glp_simplex returned %d\n", ret); + goto done; + } + ret = glp_get_status(lp); + if (ret != GLP_OPT) + { if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("Warning: glp_get_status returned %d\n", ret); + goto done; + } + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("delta = %g\n", lp->obj_val); + /* check if the basic solution is integer feasible; note that it + may be so even if the minimial distance is positive */ + tol = 0.3 * T->parm->tol_int; + for (k = 1; k <= nv; k++) + { col = lp->col[var[k].j]; + if (tol < col->prim && col->prim < 1.0 - tol) break; + } + if (k > nv) + { /* okay; the basic solution seems to be integer feasible */ + double *x = xcalloc(1+n, sizeof(double)); + for (j = 1; j <= n; j++) + { x[j] = lp->col[j]->prim; + if (P->col[j]->kind == GLP_IV) x[j] = floor(x[j] + 0.5); + } +#if 1 /* modified by xypron <xypron.glpk@gmx.de> */ + /* reset direction and right-hand side of objective */ + lp->c0 = P->c0; + lp->dir = P->dir; + /* fix integer variables */ + for (k = 1; k <= nv; k++) +#if 0 /* 18/VI-2013; fixed by mao + * this bug causes numerical instability, because column statuses + * are not changed appropriately */ + { lp->col[var[k].j]->lb = x[var[k].j]; + lp->col[var[k].j]->ub = x[var[k].j]; + lp->col[var[k].j]->type = GLP_FX; + } +#else + glp_set_col_bnds(lp, var[k].j, GLP_FX, x[var[k].j], 0.); +#endif + /* copy original objective function */ + for (j = 1; j <= n; j++) + lp->col[j]->coef = P->col[j]->coef; + /* solve original LP and copy result */ + ret = glp_simplex(lp, &parm); + if (ret != 0) + { if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("Warning: glp_simplex returned %d\n", ret); +#if 1 /* 17/III-2016: fix memory leak */ + xfree(x); +#endif + goto done; + } + ret = glp_get_status(lp); + if (ret != GLP_OPT) + { if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("Warning: glp_get_status returned %d\n", ret); +#if 1 /* 17/III-2016: fix memory leak */ + xfree(x); +#endif + goto done; + } + for (j = 1; j <= n; j++) + if (P->col[j]->kind != GLP_IV) x[j] = lp->col[j]->prim; +#endif + ret = glp_ios_heur_sol(T, x); + xfree(x); + if (ret == 0) + { /* the integer solution is accepted */ + if (ios_is_hopeful(T, T->curr->bound)) + { /* it is reasonable to apply the heuristic once again */ + goto more; + } + else + { /* the best known integer feasible solution just found + is close to optimal solution to LP relaxation */ + goto done; + } + } + } + /* the basic solution is fractional */ + if (dist == DBL_MAX || + lp->obj_val <= dist - 1e-6 * (1.0 + dist)) + { /* the distance is reducing */ + nfail = 0, dist = lp->obj_val; + } + else + { /* improving the distance failed */ + nfail++; + } + if (nfail < 3) goto loop; + if (npass < 5) goto pass; +done: /* delete working objects */ + if (lp != NULL) glp_delete_prob(lp); + if (var != NULL) xfree(var); + if (rand != NULL) rng_delete_rand(rand); + return; +} + +/* eof */ |