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)
#if 0 /* 16/II-2012 */
{ 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();
}
#else
{ size_t total;
glp_mem_usage(NULL, NULL, &total, NULL);
xprintf("Time used: %.1f secs. Memory used: %.1f Mb.\n",
xdifftime(xtime(), T->tm_beg), (double)total / 1048576.0);
ttt = xtime();
}
#endif
/* 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;
}
int lpx_intopt(LPX *_mip)
{ IPP *ipp = NULL;
LPX *orig = _mip, *prob = NULL;
int orig_m, orig_n, i, j, ret, i_stat;
/* the problem must be of MIP class */
if (lpx_get_class(orig) != LPX_MIP)
{ print("lpx_intopt: problem is not of MIP class");
ret = LPX_E_FAULT;
goto done;
}
/* the problem must have at least one row and one column */
orig_m = lpx_get_num_rows(orig);
orig_n = lpx_get_num_cols(orig);
if (!(orig_m > 0 && orig_n > 0))
{ print("lpx_intopt: problem has no rows/columns");
ret = LPX_E_FAULT;
goto done;
}
/* check that each double-bounded row and column has bounds */
for (i = 1; i <= orig_m; i++)
{ if (lpx_get_row_type(orig, i) == LPX_DB)
{ if (lpx_get_row_lb(orig, i) >= lpx_get_row_ub(orig, i))
{ print("lpx_intopt: row %d has incorrect bounds", i);
ret = LPX_E_FAULT;
goto done;
}
}
}
for (j = 1; j <= orig_n; j++)
{ if (lpx_get_col_type(orig, j) == LPX_DB)
{ if (lpx_get_col_lb(orig, j) >= lpx_get_col_ub(orig, j))
{ print("lpx_intopt: column %d has incorrect bounds", j);
ret = LPX_E_FAULT;
goto done;
}
}
}
/* bounds of all integer variables must be integral */
for (j = 1; j <= orig_n; j++)
{ int type;
double lb, ub;
if (lpx_get_col_kind(orig, j) != LPX_IV) continue;
type = lpx_get_col_type(orig, j);
if (type == LPX_LO || type == LPX_DB || type == LPX_FX)
{ lb = lpx_get_col_lb(orig, j);
if (lb != floor(lb))
{ print("lpx_intopt: integer column %d has non-integer low"
"er bound or fixed value %g", j, lb);
ret = LPX_E_FAULT;
goto done;
}
}
if (type == LPX_UP || type == LPX_DB)
{ ub = lpx_get_col_ub(orig, j);
if (ub != floor(ub))
{ print("lpx_intopt: integer column %d has non-integer upp"
"er bound %g", j, ub);
ret = LPX_E_FAULT;
goto done;
}
}
}
/* reset the status of MIP solution */
lpx_put_mip_soln(orig, LPX_I_UNDEF, NULL, NULL);
/* create MIP presolver workspace */
ipp = ipp_create_wksp();
/* load the original problem into the presolver workspace */
ipp_load_orig(ipp, orig);
/* perform basic MIP presolve analysis */
switch (ipp_basic_tech(ipp))
{ case 0:
/* no infeasibility is detected */
break;
case 1:
nopfs: /* primal infeasibility is detected */
print("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION");
ret = LPX_E_NOPFS;
goto done;
case 2:
/* dual infeasibility is detected */
nodfs: print("LP RELAXATION HAS NO DUAL FEASIBLE SOLUTION");
ret = LPX_E_NODFS;
goto done;
default:
insist(ipp != ipp);
}
/* reduce column bounds */
switch (ipp_reduce_bnds(ipp))
{ case 0: break;
case 1: goto nopfs;
default: insist(ipp != ipp);
}
/* perform basic MIP presolve analysis */
switch (ipp_basic_tech(ipp))
{ case 0: break;
case 1: goto nopfs;
case 2: goto nodfs;
default: insist(ipp != ipp);
}
/* replace general integer variables by sum of binary variables,
if required */
if (lpx_get_int_parm(orig, LPX_K_BINARIZE))
ipp_binarize(ipp);
/* perform coefficient reduction */
ipp_reduction(ipp);
/* if the resultant problem is empty, it has an empty solution,
which is optimal */
if (ipp->row_ptr == NULL || ipp->col_ptr == NULL)
{ insist(ipp->row_ptr == NULL);
insist(ipp->col_ptr == NULL);
print("Objective value = %.10g",
ipp->orig_dir == LPX_MIN ? +ipp->c0 : -ipp->c0);
print("INTEGER OPTIMAL SOLUTION FOUND BY MIP PRESOLVER");
/* allocate recovered solution segment */
ipp->col_stat = ucalloc(1+ipp->ncols, sizeof(int));
ipp->col_mipx = ucalloc(1+ipp->ncols, sizeof(double));
for (j = 1; j <= ipp->ncols; j++) ipp->col_stat[j] = 0;
/* perform MIP postsolve processing */
ipp_postsolve(ipp);
/* unload recovered MIP solution and store it in the original
problem object */
ipp_unload_sol(ipp, orig, LPX_I_OPT);
ret = LPX_E_OK;
goto done;
}
/* build resultant MIP problem object */
prob = ipp_build_prob(ipp);
/* display some statistics */
{ int m = lpx_get_num_rows(prob);
int n = lpx_get_num_cols(prob);
int nnz = lpx_get_num_nz(prob);
int ni = lpx_get_num_int(prob);
int nb = lpx_get_num_bin(prob);
char s[50];
print("lpx_intopt: presolved MIP has %d row%s, %d column%s, %d"
" non-zero%s", m, m == 1 ? "" : "s", n, n == 1 ? "" : "s",
nnz, nnz == 1 ? "" : "s");
if (nb == 0)
strcpy(s, "none of");
else if (ni == 1 && nb == 1)
strcpy(s, "");
else if (nb == 1)
strcpy(s, "one of");
else if (nb == ni)
strcpy(s, "all of");
else
sprintf(s, "%d of", nb);
print("lpx_intopt: %d integer column%s, %s which %s binary",
ni, ni == 1 ? "" : "s", s, nb == 1 ? "is" : "are");
}
/* inherit some control parameters and statistics */
lpx_set_int_parm(prob, LPX_K_PRICE, lpx_get_int_parm(orig,
LPX_K_PRICE));
lpx_set_real_parm(prob, LPX_K_RELAX, lpx_get_real_parm(orig,
LPX_K_RELAX));
lpx_set_real_parm(prob, LPX_K_TOLBND, lpx_get_real_parm(orig,
LPX_K_TOLBND));
lpx_set_real_parm(prob, LPX_K_TOLDJ, lpx_get_real_parm(orig,
LPX_K_TOLDJ));
lpx_set_real_parm(prob, LPX_K_TOLPIV, lpx_get_real_parm(orig,
LPX_K_TOLPIV));
lpx_set_int_parm(prob, LPX_K_ITLIM, lpx_get_int_parm(orig,
LPX_K_ITLIM));
lpx_set_int_parm(prob, LPX_K_ITCNT, lpx_get_int_parm(orig,
LPX_K_ITCNT));
lpx_set_real_parm(prob, LPX_K_TMLIM, lpx_get_real_parm(orig,
LPX_K_TMLIM));
lpx_set_int_parm(prob, LPX_K_BRANCH, lpx_get_int_parm(orig,
LPX_K_BRANCH));
lpx_set_int_parm(prob, LPX_K_BTRACK, lpx_get_int_parm(orig,
LPX_K_BTRACK));
lpx_set_real_parm(prob, LPX_K_TOLINT, lpx_get_real_parm(orig,
LPX_K_TOLINT));
lpx_set_real_parm(prob, LPX_K_TOLOBJ, lpx_get_real_parm(orig,
LPX_K_TOLOBJ));
/* build an advanced initial basis */
lpx_adv_basis(prob);
/* solve LP relaxation */
print("Solving LP relaxation...");
switch (lpx_simplex(prob))
{ case LPX_E_OK:
break;
case LPX_E_ITLIM:
ret = LPX_E_ITLIM;
goto done;
case LPX_E_TMLIM:
ret = LPX_E_TMLIM;
goto done;
default:
print("lpx_intopt: cannot solve LP relaxation");
ret = LPX_E_SING;
goto done;
}
/* analyze status of the basic solution */
switch (lpx_get_status(prob))
{ case LPX_OPT:
break;
case LPX_NOFEAS:
ret = LPX_E_NOPFS;
goto done;
case LPX_UNBND:
ret = LPX_E_NODFS;
goto done;
default:
insist(prob != prob);
}
/* generate cutting planes, if necessary */
if (lpx_get_int_parm(orig, LPX_K_USECUTS))
{ ret = generate_cuts(prob);
if (ret != LPX_E_OK) goto done;
}
/* call the branch-and-bound solver */
ret = lpx_integer(prob);
/* determine status of MIP solution */
i_stat = lpx_mip_status(prob);
if (i_stat == LPX_I_OPT || i_stat == LPX_I_FEAS)
{ /* load MIP solution of the resultant problem into presolver
workspace */
ipp_load_sol(ipp, prob);
/* perform MIP postsolve processing */
ipp_postsolve(ipp);
/* unload recovered MIP solution and store it in the original
problem object */
ipp_unload_sol(ipp, orig, i_stat);
}
else
{ /* just set the status of MIP solution */
lpx_put_mip_soln(orig, i_stat, NULL, NULL);
}
done: /* copy back statistics about spent resources */
if (prob != NULL)
{ lpx_set_int_parm(orig, LPX_K_ITLIM, lpx_get_int_parm(prob,
LPX_K_ITLIM));
lpx_set_int_parm(orig, LPX_K_ITCNT, lpx_get_int_parm(prob,
LPX_K_ITCNT));
lpx_set_real_parm(orig, LPX_K_TMLIM, lpx_get_real_parm(prob,
LPX_K_TMLIM));
}
/* delete the resultant problem object */
if (prob != NULL) lpx_delete_prob(prob);
/* delete MIP presolver workspace */
if (ipp != NULL) ipp_delete_wksp(ipp);
return ret;
}