diff -r d59bea55db9b -r c445c931472f src/glpios03.c --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/src/glpios03.c Mon Dec 06 13:09:21 2010 +0100 @@ -0,0 +1,1155 @@ +/* glpios03.c (branch-and-cut driver) */ + +/*********************************************************************** +* This code is part of GLPK (GNU Linear Programming Kit). +* +* Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, +* 2009, 2010 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" + +/*********************************************************************** +* show_progress - display current progress of the search +* +* This routine displays some information about current progress of the +* search. +* +* The information includes: +* +* the current number of iterations performed by the simplex solver; +* +* the objective value for the best known integer feasible solution, +* which is upper (minimization) or lower (maximization) global bound +* for optimal solution of the original mip problem; +* +* the best local bound for active nodes, which is lower (minimization) +* or upper (maximization) global bound for optimal solution of the +* original mip problem; +* +* the relative mip gap, in percents; +* +* the number of open (active) subproblems; +* +* the number of completely explored subproblems, i.e. whose nodes have +* been removed from the tree. */ + +static void show_progress(glp_tree *T, int bingo) +{ int p; + double temp; + char best_mip[50], best_bound[50], *rho, rel_gap[50]; + /* format the best known integer feasible solution */ + if (T->mip->mip_stat == GLP_FEAS) + sprintf(best_mip, "%17.9e", T->mip->mip_obj); + else + sprintf(best_mip, "%17s", "not found yet"); + /* determine reference number of an active subproblem whose local + bound is best */ + p = ios_best_node(T); + /* format the best bound */ + if (p == 0) + sprintf(best_bound, "%17s", "tree is empty"); + else + { temp = T->slot[p].node->bound; + if (temp == -DBL_MAX) + sprintf(best_bound, "%17s", "-inf"); + else if (temp == +DBL_MAX) + sprintf(best_bound, "%17s", "+inf"); + else + sprintf(best_bound, "%17.9e", temp); + } + /* choose the relation sign between global bounds */ + if (T->mip->dir == GLP_MIN) + rho = ">="; + else if (T->mip->dir == GLP_MAX) + rho = "<="; + else + xassert(T != T); + /* format the relative mip gap */ + temp = ios_relative_gap(T); + if (temp == 0.0) + sprintf(rel_gap, " 0.0%%"); + else if (temp < 0.001) + sprintf(rel_gap, "< 0.1%%"); + else if (temp <= 9.999) + sprintf(rel_gap, "%5.1f%%", 100.0 * temp); + else + sprintf(rel_gap, "%6s", ""); + /* display progress of the search */ + xprintf("+%6d: %s %s %s %s %s (%d; %d)\n", + T->mip->it_cnt, bingo ? ">>>>>" : "mip =", best_mip, rho, + best_bound, rel_gap, T->a_cnt, T->t_cnt - T->n_cnt); + T->tm_lag = xtime(); + return; +} + +/*********************************************************************** +* is_branch_hopeful - check if specified branch is hopeful +* +* This routine checks if the specified subproblem can have an integer +* optimal solution which is better than the best known one. +* +* The check is based on comparison of the local objective bound stored +* in the subproblem descriptor and the incumbent objective value which +* is the global objective bound. +* +* If there is a chance that the specified subproblem can have a better +* integer optimal solution, the routine returns non-zero. Otherwise, if +* the corresponding branch can pruned, zero is returned. */ + +static int is_branch_hopeful(glp_tree *T, int p) +{ xassert(1 <= p && p <= T->nslots); + xassert(T->slot[p].node != NULL); + return ios_is_hopeful(T, T->slot[p].node->bound); +} + +/*********************************************************************** +* check_integrality - check integrality of basic solution +* +* This routine checks if the basic solution of LP relaxation of the +* current subproblem satisfies to integrality conditions, i.e. that all +* variables of integer kind have integral primal values. (The solution +* is assumed to be optimal.) +* +* For each variable of integer kind the routine computes the following +* quantity: +* +* ii(x[j]) = min(x[j] - floor(x[j]), ceil(x[j]) - x[j]), (1) +* +* which is a measure of the integer infeasibility (non-integrality) of +* x[j] (for example, ii(2.1) = 0.1, ii(3.7) = 0.3, ii(5.0) = 0). It is +* understood that 0 <= ii(x[j]) <= 0.5, and variable x[j] is integer +* feasible if ii(x[j]) = 0. However, due to floating-point arithmetic +* the routine checks less restrictive condition: +* +* ii(x[j]) <= tol_int, (2) +* +* where tol_int is a given tolerance (small positive number) and marks +* each variable which does not satisfy to (2) as integer infeasible by +* setting its fractionality flag. +* +* In order to characterize integer infeasibility of the basic solution +* in the whole the routine computes two parameters: ii_cnt, which is +* the number of variables with the fractionality flag set, and ii_sum, +* which is the sum of integer infeasibilities (1). */ + +static void check_integrality(glp_tree *T) +{ glp_prob *mip = T->mip; + int j, type, ii_cnt = 0; + double lb, ub, x, temp1, temp2, ii_sum = 0.0; + /* walk through the set of columns (structural variables) */ + for (j = 1; j <= mip->n; j++) + { GLPCOL *col = mip->col[j]; + T->non_int[j] = 0; + /* if the column is not integer, skip it */ + if (col->kind != GLP_IV) continue; + /* if the column is non-basic, it is integer feasible */ + if (col->stat != GLP_BS) continue; + /* obtain the type and bounds of the column */ + type = col->type, lb = col->lb, ub = col->ub; + /* obtain value of the column in optimal basic solution */ + x = col->prim; + /* if the column's primal value is close to the lower bound, + the column is integer feasible within given tolerance */ + if (type == GLP_LO || type == GLP_DB || type == GLP_FX) + { temp1 = lb - T->parm->tol_int; + temp2 = lb + T->parm->tol_int; + if (temp1 <= x && x <= temp2) continue; +#if 0 + /* the lower bound must not be violated */ + xassert(x >= lb); +#else + if (x < lb) continue; +#endif + } + /* if the column's primal value is close to the upper bound, + the column is integer feasible within given tolerance */ + if (type == GLP_UP || type == GLP_DB || type == GLP_FX) + { temp1 = ub - T->parm->tol_int; + temp2 = ub + T->parm->tol_int; + if (temp1 <= x && x <= temp2) continue; +#if 0 + /* the upper bound must not be violated */ + xassert(x <= ub); +#else + if (x > ub) continue; +#endif + } + /* if the column's primal value is close to nearest integer, + the column is integer feasible within given tolerance */ + temp1 = floor(x + 0.5) - T->parm->tol_int; + temp2 = floor(x + 0.5) + T->parm->tol_int; + if (temp1 <= x && x <= temp2) continue; + /* otherwise the column is integer infeasible */ + T->non_int[j] = 1; + /* increase the number of fractional-valued columns */ + ii_cnt++; + /* compute the sum of integer infeasibilities */ + temp1 = x - floor(x); + temp2 = ceil(x) - x; + xassert(temp1 > 0.0 && temp2 > 0.0); + ii_sum += (temp1 <= temp2 ? temp1 : temp2); + } + /* store ii_cnt and ii_sum to the current problem descriptor */ + xassert(T->curr != NULL); + T->curr->ii_cnt = ii_cnt; + T->curr->ii_sum = ii_sum; + /* and also display these parameters */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + { if (ii_cnt == 0) + xprintf("There are no fractional columns\n"); + else if (ii_cnt == 1) + xprintf("There is one fractional column, integer infeasibil" + "ity is %.3e\n", ii_sum); + else + xprintf("There are %d fractional columns, integer infeasibi" + "lity is %.3e\n", ii_cnt, ii_sum); + } + return; +} + +/*********************************************************************** +* record_solution - record better integer feasible solution +* +* This routine records optimal basic solution of LP relaxation of the +* current subproblem, which being integer feasible is better than the +* best known integer feasible solution. */ + +static void record_solution(glp_tree *T) +{ glp_prob *mip = T->mip; + int i, j; + mip->mip_stat = GLP_FEAS; + mip->mip_obj = mip->obj_val; + for (i = 1; i <= mip->m; i++) + { GLPROW *row = mip->row[i]; + row->mipx = row->prim; + } + for (j = 1; j <= mip->n; j++) + { GLPCOL *col = mip->col[j]; + if (col->kind == GLP_CV) + col->mipx = col->prim; + else if (col->kind == GLP_IV) + { /* value of the integer column must be integral */ + col->mipx = floor(col->prim + 0.5); + } + else + xassert(col != col); + } + T->sol_cnt++; + return; +} + +/*********************************************************************** +* fix_by_red_cost - fix non-basic integer columns by reduced costs +* +* This routine fixes some non-basic integer columns if their reduced +* costs indicate that increasing (decreasing) the column at least by +* one involves the objective value becoming worse than the incumbent +* objective value. */ + +static void fix_by_red_cost(glp_tree *T) +{ glp_prob *mip = T->mip; + int j, stat, fixed = 0; + double obj, lb, ub, dj; + /* the global bound must exist */ + xassert(T->mip->mip_stat == GLP_FEAS); + /* basic solution of LP relaxation must be optimal */ + xassert(mip->pbs_stat == GLP_FEAS && mip->dbs_stat == GLP_FEAS); + /* determine the objective function value */ + obj = mip->obj_val; + /* walk through the column list */ + for (j = 1; j <= mip->n; j++) + { GLPCOL *col = mip->col[j]; + /* if the column is not integer, skip it */ + if (col->kind != GLP_IV) continue; + /* obtain bounds of j-th column */ + lb = col->lb, ub = col->ub; + /* and determine its status and reduced cost */ + stat = col->stat, dj = col->dual; + /* analyze the reduced cost */ + switch (mip->dir) + { case GLP_MIN: + /* minimization */ + if (stat == GLP_NL) + { /* j-th column is non-basic on its lower bound */ + if (dj < 0.0) dj = 0.0; + if (obj + dj >= mip->mip_obj) + glp_set_col_bnds(mip, j, GLP_FX, lb, lb), fixed++; + } + else if (stat == GLP_NU) + { /* j-th column is non-basic on its upper bound */ + if (dj > 0.0) dj = 0.0; + if (obj - dj >= mip->mip_obj) + glp_set_col_bnds(mip, j, GLP_FX, ub, ub), fixed++; + } + break; + case GLP_MAX: + /* maximization */ + if (stat == GLP_NL) + { /* j-th column is non-basic on its lower bound */ + if (dj > 0.0) dj = 0.0; + if (obj + dj <= mip->mip_obj) + glp_set_col_bnds(mip, j, GLP_FX, lb, lb), fixed++; + } + else if (stat == GLP_NU) + { /* j-th column is non-basic on its upper bound */ + if (dj < 0.0) dj = 0.0; + if (obj - dj <= mip->mip_obj) + glp_set_col_bnds(mip, j, GLP_FX, ub, ub), fixed++; + } + break; + default: + xassert(T != T); + } + } + if (T->parm->msg_lev >= GLP_MSG_DBG) + { if (fixed == 0) + /* nothing to say */; + else if (fixed == 1) + xprintf("One column has been fixed by reduced cost\n"); + else + xprintf("%d columns have been fixed by reduced costs\n", + fixed); + } + /* fixing non-basic columns on their current bounds does not + change the basic solution */ + xassert(mip->pbs_stat == GLP_FEAS && mip->dbs_stat == GLP_FEAS); + return; +} + +/*********************************************************************** +* branch_on - perform branching on specified variable +* +* This routine performs branching on j-th column (structural variable) +* of the current subproblem. The specified column must be of integer +* kind and must have a fractional value in optimal basic solution of +* LP relaxation of the current subproblem (i.e. only columns for which +* the flag non_int[j] is set are valid candidates to branch on). +* +* Let x be j-th structural variable, and beta be its primal fractional +* value in the current basic solution. Branching on j-th variable is +* dividing the current subproblem into two new subproblems, which are +* identical to the current subproblem with the following exception: in +* the first subproblem that begins the down-branch x has a new upper +* bound x <= floor(beta), and in the second subproblem that begins the +* up-branch x has a new lower bound x >= ceil(beta). +* +* Depending on estimation of local bounds for down- and up-branches +* this routine returns the following: +* +* 0 - both branches have been created; +* 1 - one branch is hopeless and has been pruned, so now the current +* subproblem is other branch; +* 2 - both branches are hopeless and have been pruned; new subproblem +* selection is needed to continue the search. */ + +static int branch_on(glp_tree *T, int j, int next) +{ glp_prob *mip = T->mip; + IOSNPD *node; + int m = mip->m; + int n = mip->n; + int type, dn_type, up_type, dn_bad, up_bad, p, ret, clone[1+2]; + double lb, ub, beta, new_ub, new_lb, dn_lp, up_lp, dn_bnd, up_bnd; + /* determine bounds and value of x[j] in optimal solution to LP + relaxation of the current subproblem */ + xassert(1 <= j && j <= n); + type = mip->col[j]->type; + lb = mip->col[j]->lb; + ub = mip->col[j]->ub; + beta = mip->col[j]->prim; + /* determine new bounds of x[j] for down- and up-branches */ + new_ub = floor(beta); + new_lb = ceil(beta); + switch (type) + { case GLP_FR: + dn_type = GLP_UP; + up_type = GLP_LO; + break; + case GLP_LO: + xassert(lb <= new_ub); + dn_type = (lb == new_ub ? GLP_FX : GLP_DB); + xassert(lb + 1.0 <= new_lb); + up_type = GLP_LO; + break; + case GLP_UP: + xassert(new_ub <= ub - 1.0); + dn_type = GLP_UP; + xassert(new_lb <= ub); + up_type = (new_lb == ub ? GLP_FX : GLP_DB); + break; + case GLP_DB: + xassert(lb <= new_ub && new_ub <= ub - 1.0); + dn_type = (lb == new_ub ? GLP_FX : GLP_DB); + xassert(lb + 1.0 <= new_lb && new_lb <= ub); + up_type = (new_lb == ub ? GLP_FX : GLP_DB); + break; + default: + xassert(type != type); + } + /* compute local bounds to LP relaxation for both branches */ + ios_eval_degrad(T, j, &dn_lp, &up_lp); + /* and improve them by rounding */ + dn_bnd = ios_round_bound(T, dn_lp); + up_bnd = ios_round_bound(T, up_lp); + /* check local bounds for down- and up-branches */ + dn_bad = !ios_is_hopeful(T, dn_bnd); + up_bad = !ios_is_hopeful(T, up_bnd); + if (dn_bad && up_bad) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Both down- and up-branches are hopeless\n"); + ret = 2; + goto done; + } + else if (up_bad) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Up-branch is hopeless\n"); + glp_set_col_bnds(mip, j, dn_type, lb, new_ub); + T->curr->lp_obj = dn_lp; + if (mip->dir == GLP_MIN) + { if (T->curr->bound < dn_bnd) + T->curr->bound = dn_bnd; + } + else if (mip->dir == GLP_MAX) + { if (T->curr->bound > dn_bnd) + T->curr->bound = dn_bnd; + } + else + xassert(mip != mip); + ret = 1; + goto done; + } + else if (dn_bad) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Down-branch is hopeless\n"); + glp_set_col_bnds(mip, j, up_type, new_lb, ub); + T->curr->lp_obj = up_lp; + if (mip->dir == GLP_MIN) + { if (T->curr->bound < up_bnd) + T->curr->bound = up_bnd; + } + else if (mip->dir == GLP_MAX) + { if (T->curr->bound > up_bnd) + T->curr->bound = up_bnd; + } + else + xassert(mip != mip); + ret = 1; + goto done; + } + /* both down- and up-branches seem to be hopeful */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Branching on column %d, primal value is %.9e\n", + j, beta); + /* determine the reference number of the current subproblem */ + xassert(T->curr != NULL); + p = T->curr->p; + T->curr->br_var = j; + T->curr->br_val = beta; + /* freeze the current subproblem */ + ios_freeze_node(T); + /* create two clones of the current subproblem; the first clone + begins the down-branch, the second one begins the up-branch */ + ios_clone_node(T, p, 2, clone); + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Node %d begins down branch, node %d begins up branch " + "\n", clone[1], clone[2]); + /* set new upper bound of j-th column in the down-branch */ + node = T->slot[clone[1]].node; + xassert(node != NULL); + xassert(node->up != NULL); + xassert(node->b_ptr == NULL); + node->b_ptr = dmp_get_atom(T->pool, sizeof(IOSBND)); + node->b_ptr->k = m + j; + node->b_ptr->type = (unsigned char)dn_type; + node->b_ptr->lb = lb; + node->b_ptr->ub = new_ub; + node->b_ptr->next = NULL; + node->lp_obj = dn_lp; + if (mip->dir == GLP_MIN) + { if (node->bound < dn_bnd) + node->bound = dn_bnd; + } + else if (mip->dir == GLP_MAX) + { if (node->bound > dn_bnd) + node->bound = dn_bnd; + } + else + xassert(mip != mip); + /* set new lower bound of j-th column in the up-branch */ + node = T->slot[clone[2]].node; + xassert(node != NULL); + xassert(node->up != NULL); + xassert(node->b_ptr == NULL); + node->b_ptr = dmp_get_atom(T->pool, sizeof(IOSBND)); + node->b_ptr->k = m + j; + node->b_ptr->type = (unsigned char)up_type; + node->b_ptr->lb = new_lb; + node->b_ptr->ub = ub; + node->b_ptr->next = NULL; + node->lp_obj = up_lp; + if (mip->dir == GLP_MIN) + { if (node->bound < up_bnd) + node->bound = up_bnd; + } + else if (mip->dir == GLP_MAX) + { if (node->bound > up_bnd) + node->bound = up_bnd; + } + else + xassert(mip != mip); + /* suggest the subproblem to be solved next */ + xassert(T->child == 0); + if (next == GLP_NO_BRNCH) + T->child = 0; + else if (next == GLP_DN_BRNCH) + T->child = clone[1]; + else if (next == GLP_UP_BRNCH) + T->child = clone[2]; + else + xassert(next != next); + ret = 0; +done: return ret; +} + +/*********************************************************************** +* cleanup_the_tree - prune hopeless branches from the tree +* +* This routine walks through the active list and checks the local +* bound for every active subproblem. If the local bound indicates that +* the subproblem cannot have integer optimal solution better than the +* incumbent objective value, the routine deletes such subproblem that, +* in turn, involves pruning the corresponding branch of the tree. */ + +static void cleanup_the_tree(glp_tree *T) +{ IOSNPD *node, *next_node; + int count = 0; + /* the global bound must exist */ + xassert(T->mip->mip_stat == GLP_FEAS); + /* walk through the list of active subproblems */ + for (node = T->head; node != NULL; node = next_node) + { /* deleting some active problem node may involve deleting its + parents recursively; however, all its parents being created + *before* it are always *precede* it in the node list, so + the next problem node is never affected by such deletion */ + next_node = node->next; + /* if the branch is hopeless, prune it */ + if (!is_branch_hopeful(T, node->p)) + ios_delete_node(T, node->p), count++; + } + if (T->parm->msg_lev >= GLP_MSG_DBG) + { if (count == 1) + xprintf("One hopeless branch has been pruned\n"); + else if (count > 1) + xprintf("%d hopeless branches have been pruned\n", count); + } + return; +} + +/**********************************************************************/ + +static void generate_cuts(glp_tree *T) +{ /* generate generic cuts with built-in generators */ + if (!(T->parm->mir_cuts == GLP_ON || + T->parm->gmi_cuts == GLP_ON || + T->parm->cov_cuts == GLP_ON || + T->parm->clq_cuts == GLP_ON)) goto done; +#if 1 /* 20/IX-2008 */ + { int i, max_cuts, added_cuts; + max_cuts = T->n; + if (max_cuts < 1000) max_cuts = 1000; + added_cuts = 0; + for (i = T->orig_m+1; i <= T->mip->m; i++) + { if (T->mip->row[i]->origin == GLP_RF_CUT) + added_cuts++; + } + /* xprintf("added_cuts = %d\n", added_cuts); */ + if (added_cuts >= max_cuts) goto done; + } +#endif + /* generate and add to POOL all cuts violated by x* */ + if (T->parm->gmi_cuts == GLP_ON) + { if (T->curr->changed < 5) + ios_gmi_gen(T); + } + if (T->parm->mir_cuts == GLP_ON) + { xassert(T->mir_gen != NULL); + ios_mir_gen(T, T->mir_gen); + } + if (T->parm->cov_cuts == GLP_ON) + { /* cover cuts works well along with mir cuts */ + /*if (T->round <= 5)*/ + ios_cov_gen(T); + } + if (T->parm->clq_cuts == GLP_ON) + { if (T->clq_gen != NULL) + { if (T->curr->level == 0 && T->curr->changed < 50 || + T->curr->level > 0 && T->curr->changed < 5) + ios_clq_gen(T, T->clq_gen); + } + } +done: return; +} + +/**********************************************************************/ + +static void remove_cuts(glp_tree *T) +{ /* remove inactive cuts (some valueable globally valid cut might + be saved in the global cut pool) */ + int i, cnt = 0, *num = NULL; + xassert(T->curr != NULL); + for (i = T->orig_m+1; i <= T->mip->m; i++) + { if (T->mip->row[i]->origin == GLP_RF_CUT && + T->mip->row[i]->level == T->curr->level && + T->mip->row[i]->stat == GLP_BS) + { if (num == NULL) + num = xcalloc(1+T->mip->m, sizeof(int)); + num[++cnt] = i; + } + } + if (cnt > 0) + { glp_del_rows(T->mip, cnt, num); +#if 0 + xprintf("%d inactive cut(s) removed\n", cnt); +#endif + xfree(num); + xassert(glp_factorize(T->mip) == 0); + } + return; +} + +/**********************************************************************/ + +static void display_cut_info(glp_tree *T) +{ glp_prob *mip = T->mip; + int i, gmi = 0, mir = 0, cov = 0, clq = 0, app = 0; + for (i = mip->m; i > 0; i--) + { GLPROW *row; + row = mip->row[i]; + /* if (row->level < T->curr->level) break; */ + if (row->origin == GLP_RF_CUT) + { if (row->klass == GLP_RF_GMI) + gmi++; + else if (row->klass == GLP_RF_MIR) + mir++; + else if (row->klass == GLP_RF_COV) + cov++; + else if (row->klass == GLP_RF_CLQ) + clq++; + else + app++; + } + } + xassert(T->curr != NULL); + if (gmi + mir + cov + clq + app > 0) + { xprintf("Cuts on level %d:", T->curr->level); + if (gmi > 0) xprintf(" gmi = %d;", gmi); + if (mir > 0) xprintf(" mir = %d;", mir); + if (cov > 0) xprintf(" cov = %d;", cov); + if (clq > 0) xprintf(" clq = %d;", clq); + if (app > 0) xprintf(" app = %d;", app); + xprintf("\n"); + } + return; +} + +/*********************************************************************** +* NAME +* +* ios_driver - branch-and-cut driver +* +* SYNOPSIS +* +* #include "glpios.h" +* int ios_driver(glp_tree *T); +* +* DESCRIPTION +* +* The routine ios_driver is a branch-and-cut driver. It controls the +* MIP solution process. +* +* RETURNS +* +* 0 The MIP problem instance has been successfully solved. This code +* does not necessarily mean that the solver has found optimal +* solution. It only means that the solution process was successful. +* +* GLP_EFAIL +* The search was prematurely terminated due to the solver failure. +* +* GLP_EMIPGAP +* The search was prematurely terminated, because the relative mip +* gap tolerance has been reached. +* +* GLP_ETMLIM +* The search was prematurely terminated, because the time limit has +* been exceeded. +* +* GLP_ESTOP +* The search was prematurely terminated by application. */ + +int ios_driver(glp_tree *T) +{ int p, curr_p, p_stat, d_stat, ret; +#if 1 /* carry out to glp_tree */ + int pred_p = 0; + /* if the current subproblem has been just created due to + branching, pred_p is the reference number of its parent + subproblem, otherwise pred_p is zero */ +#endif + glp_long ttt = T->tm_beg; +#if 0 + ((glp_iocp *)T->parm)->msg_lev = GLP_MSG_DBG; +#endif + /* on entry to the B&B driver it is assumed that the active list + contains the only active (i.e. root) subproblem, which is the + original MIP problem to be solved */ +loop: /* main loop starts here */ + /* at this point the current subproblem does not exist */ + xassert(T->curr == NULL); + /* if the active list is empty, the search is finished */ + if (T->head == NULL) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Active list is empty!\n"); + xassert(dmp_in_use(T->pool).lo == 0); + ret = 0; + goto done; + } + /* select some active subproblem to continue the search */ + xassert(T->next_p == 0); + /* let the application program select subproblem */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_ISELECT; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + } + if (T->next_p != 0) + { /* the application program has selected something */ + ; + } + else if (T->a_cnt == 1) + { /* the only active subproblem exists, so select it */ + xassert(T->head->next == NULL); + T->next_p = T->head->p; + } + else if (T->child != 0) + { /* select one of branching childs suggested by the branching + heuristic */ + T->next_p = T->child; + } + else + { /* select active subproblem as specified by the backtracking + technique option */ + T->next_p = ios_choose_node(T); + } + /* the active subproblem just selected becomes current */ + ios_revive_node(T, T->next_p); + T->next_p = T->child = 0; + /* invalidate pred_p, if it is not the reference number of the + parent of the current subproblem */ + if (T->curr->up != NULL && T->curr->up->p != pred_p) pred_p = 0; + /* determine the reference number of the current subproblem */ + p = T->curr->p; + if (T->parm->msg_lev >= GLP_MSG_DBG) + { xprintf("-----------------------------------------------------" + "-------------------\n"); + xprintf("Processing node %d at level %d\n", p, T->curr->level); + } + /* if it is the root subproblem, initialize cut generators */ + if (p == 1) + { if (T->parm->gmi_cuts == GLP_ON) + { if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("Gomory's cuts enabled\n"); + } + if (T->parm->mir_cuts == GLP_ON) + { if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("MIR cuts enabled\n"); + xassert(T->mir_gen == NULL); + T->mir_gen = ios_mir_init(T); + } + if (T->parm->cov_cuts == GLP_ON) + { if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("Cover cuts enabled\n"); + } + if (T->parm->clq_cuts == GLP_ON) + { xassert(T->clq_gen == NULL); + if (T->parm->msg_lev >= GLP_MSG_ALL) + xprintf("Clique cuts enabled\n"); + T->clq_gen = ios_clq_init(T); + } + } +more: /* minor loop starts here */ + /* at this point the current subproblem needs either to be solved + for the first time or re-optimized due to reformulation */ + /* display current progress of the search */ + if (T->parm->msg_lev >= GLP_MSG_DBG || + T->parm->msg_lev >= GLP_MSG_ON && + (double)(T->parm->out_frq - 1) <= + 1000.0 * xdifftime(xtime(), T->tm_lag)) + show_progress(T, 0); + if (T->parm->msg_lev >= GLP_MSG_ALL && + xdifftime(xtime(), ttt) >= 60.0) + { glp_long total; + glp_mem_usage(NULL, NULL, &total, NULL); + xprintf("Time used: %.1f secs. Memory used: %.1f Mb.\n", + xdifftime(xtime(), T->tm_beg), xltod(total) / 1048576.0); + ttt = xtime(); + } + /* check the mip gap */ + if (T->parm->mip_gap > 0.0 && + ios_relative_gap(T) <= T->parm->mip_gap) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Relative gap tolerance reached; search terminated " + "\n"); + ret = GLP_EMIPGAP; + goto done; + } + /* 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)) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Time limit exhausted; search terminated\n"); + ret = GLP_ETMLIM; + goto done; + } + /* let the application program preprocess the subproblem */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_IPREPRO; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + } + /* perform basic preprocessing */ + if (T->parm->pp_tech == GLP_PP_NONE) + ; + else if (T->parm->pp_tech == GLP_PP_ROOT) + { if (T->curr->level == 0) + { if (ios_preprocess_node(T, 100)) + goto fath; + } + } + else if (T->parm->pp_tech == GLP_PP_ALL) + { if (ios_preprocess_node(T, T->curr->level == 0 ? 100 : 10)) + goto fath; + } + else + xassert(T != T); + /* preprocessing may improve the global bound */ + if (!is_branch_hopeful(T, p)) + { xprintf("*** not tested yet ***\n"); + goto fath; + } + /* solve LP relaxation of the current subproblem */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Solving LP relaxation...\n"); + ret = ios_solve_node(T); + if (!(ret == 0 || ret == GLP_EOBJLL || ret == GLP_EOBJUL)) + { if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("ios_driver: unable to solve current LP relaxation;" + " glp_simplex returned %d\n", ret); + ret = GLP_EFAIL; + goto done; + } + /* analyze status of the basic solution to LP relaxation found */ + p_stat = T->mip->pbs_stat; + d_stat = T->mip->dbs_stat; + if (p_stat == GLP_FEAS && d_stat == GLP_FEAS) + { /* LP relaxation has optimal solution */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Found optimal solution to LP relaxation\n"); + } + else if (d_stat == GLP_NOFEAS) + { /* LP relaxation has no dual feasible solution */ + /* since the current subproblem cannot have a larger feasible + region than its parent, there is something wrong */ + if (T->parm->msg_lev >= GLP_MSG_ERR) + xprintf("ios_driver: current LP relaxation has no dual feas" + "ible solution\n"); + ret = GLP_EFAIL; + goto done; + } + else if (p_stat == GLP_INFEAS && d_stat == GLP_FEAS) + { /* LP relaxation has no primal solution which is better than + the incumbent objective value */ + xassert(T->mip->mip_stat == GLP_FEAS); + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("LP relaxation has no solution better than incumben" + "t objective value\n"); + /* prune the branch */ + goto fath; + } + else if (p_stat == GLP_NOFEAS) + { /* LP relaxation has no primal feasible solution */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("LP relaxation has no feasible solution\n"); + /* prune the branch */ + goto fath; + } + else + { /* other cases cannot appear */ + xassert(T->mip != T->mip); + } + /* at this point basic solution to LP relaxation of the current + subproblem is optimal */ + xassert(p_stat == GLP_FEAS && d_stat == GLP_FEAS); + xassert(T->curr != NULL); + T->curr->lp_obj = T->mip->obj_val; + /* thus, it defines a local bound to integer optimal solution of + the current subproblem */ + { double bound = T->mip->obj_val; + /* some local bound to the current subproblem could be already + set before, so we should only improve it */ + bound = ios_round_bound(T, bound); + if (T->mip->dir == GLP_MIN) + { if (T->curr->bound < bound) + T->curr->bound = bound; + } + else if (T->mip->dir == GLP_MAX) + { if (T->curr->bound > bound) + T->curr->bound = bound; + } + else + xassert(T->mip != T->mip); + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Local bound is %.9e\n", bound); + } + /* if the local bound indicates that integer optimal solution of + the current subproblem cannot be better than the global bound, + prune the branch */ + if (!is_branch_hopeful(T, p)) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Current branch is hopeless and can be pruned\n"); + goto fath; + } + /* let the application program generate additional rows ("lazy" + constraints) */ + xassert(T->reopt == 0); + xassert(T->reinv == 0); + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_IROWGEN; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + if (T->reopt) + { /* some rows were added; re-optimization is needed */ + T->reopt = T->reinv = 0; + goto more; + } + if (T->reinv) + { /* no rows were added, however, some inactive rows were + removed */ + T->reinv = 0; + xassert(glp_factorize(T->mip) == 0); + } + } + /* check if the basic solution is integer feasible */ + check_integrality(T); + /* if the basic solution satisfies to all integrality conditions, + it is a new, better integer feasible solution */ + if (T->curr->ii_cnt == 0) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("New integer feasible solution found\n"); + if (T->parm->msg_lev >= GLP_MSG_ALL) + display_cut_info(T); + record_solution(T); + if (T->parm->msg_lev >= GLP_MSG_ON) + show_progress(T, 1); + /* make the application program happy */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_IBINGO; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + } + /* since the current subproblem has been fathomed, prune its + branch */ + goto fath; + } + /* at this point basic solution to LP relaxation of the current + subproblem is optimal, but integer infeasible */ + /* try to fix some non-basic structural variables of integer kind + on their current bounds due to reduced costs */ + if (T->mip->mip_stat == GLP_FEAS) + fix_by_red_cost(T); + /* let the application program try to find some solution to the + original MIP with a primal heuristic */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_IHEUR; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + /* check if the current branch became hopeless */ + if (!is_branch_hopeful(T, p)) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Current branch became hopeless and can be prune" + "d\n"); + goto fath; + } + } + /* try to find solution with the feasibility pump heuristic */ + if (T->parm->fp_heur) + { xassert(T->reason == 0); + T->reason = GLP_IHEUR; + ios_feas_pump(T); + T->reason = 0; + /* check if the current branch became hopeless */ + if (!is_branch_hopeful(T, p)) + { if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Current branch became hopeless and can be prune" + "d\n"); + goto fath; + } + } + /* it's time to generate cutting planes */ + xassert(T->local != NULL); + xassert(T->local->size == 0); + /* let the application program generate some cuts; note that it + can add cuts either to the local cut pool or directly to the + current subproblem */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + T->reason = GLP_ICUTGEN; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + } + /* try to generate generic cuts with built-in generators + (as suggested by Matteo Fischetti et al. the built-in cuts + are not generated at each branching node; an intense attempt + of generating new cuts is only made at the root node, and then + a moderate effort is spent after each backtracking step) */ + if (T->curr->level == 0 || pred_p == 0) + { xassert(T->reason == 0); + T->reason = GLP_ICUTGEN; + generate_cuts(T); + T->reason = 0; + } + /* if the local cut pool is not empty, select useful cuts and add + them to the current subproblem */ + if (T->local->size > 0) + { xassert(T->reason == 0); + T->reason = GLP_ICUTGEN; + ios_process_cuts(T); + T->reason = 0; + } + /* clear the local cut pool */ + ios_clear_pool(T, T->local); + /* perform re-optimization, if necessary */ + if (T->reopt) + { T->reopt = 0; + T->curr->changed++; + goto more; + } + /* no cuts were generated; remove inactive cuts */ + remove_cuts(T); + if (T->parm->msg_lev >= GLP_MSG_ALL && T->curr->level == 0) + display_cut_info(T); + /* update history information used on pseudocost branching */ + if (T->pcost != NULL) ios_pcost_update(T); + /* it's time to perform branching */ + xassert(T->br_var == 0); + xassert(T->br_sel == 0); + /* let the application program choose variable to branch on */ + if (T->parm->cb_func != NULL) + { xassert(T->reason == 0); + xassert(T->br_var == 0); + xassert(T->br_sel == 0); + T->reason = GLP_IBRANCH; + T->parm->cb_func(T, T->parm->cb_info); + T->reason = 0; + if (T->stop) + { ret = GLP_ESTOP; + goto done; + } + } + /* if nothing has been chosen, choose some variable as specified + by the branching technique option */ + if (T->br_var == 0) + T->br_var = ios_choose_var(T, &T->br_sel); + /* perform actual branching */ + curr_p = T->curr->p; + ret = branch_on(T, T->br_var, T->br_sel); + T->br_var = T->br_sel = 0; + if (ret == 0) + { /* both branches have been created */ + pred_p = curr_p; + goto loop; + } + else if (ret == 1) + { /* one branch is hopeless and has been pruned, so now the + current subproblem is other branch */ + /* the current subproblem should be considered as a new one, + since one bound of the branching variable was changed */ + T->curr->solved = T->curr->changed = 0; + goto more; + } + else if (ret == 2) + { /* both branches are hopeless and have been pruned; new + subproblem selection is needed to continue the search */ + goto fath; + } + else + xassert(ret != ret); +fath: /* the current subproblem has been fathomed */ + if (T->parm->msg_lev >= GLP_MSG_DBG) + xprintf("Node %d fathomed\n", p); + /* freeze the current subproblem */ + ios_freeze_node(T); + /* and prune the corresponding branch of the tree */ + ios_delete_node(T, p); + /* if a new integer feasible solution has just been found, other + branches may become hopeless and therefore must be pruned */ + if (T->mip->mip_stat == GLP_FEAS) cleanup_the_tree(T); + /* new subproblem selection is needed due to backtracking */ + pred_p = 0; + goto loop; +done: /* display progress of the search on exit from the solver */ + if (T->parm->msg_lev >= GLP_MSG_ON) + show_progress(T, 0); + if (T->mir_gen != NULL) + ios_mir_term(T->mir_gen), T->mir_gen = NULL; + if (T->clq_gen != NULL) + ios_clq_term(T->clq_gen), T->clq_gen = NULL; + /* return to the calling program */ + return ret; +} + +/* eof */