static int solve_lp(glp_prob *P, const glp_smcp *parm)
{ /* solve LP directly without using the preprocessor */
int ret;
if (!glp_bf_exists(P))
{ ret = glp_factorize(P);
if (ret == 0)
;
else if (ret == GLP_EBADB)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: initial basis is invalid\n");
}
else if (ret == GLP_ESING)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: initial basis is singular\n");
}
else if (ret == GLP_ECOND)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf(
"glp_simplex: initial basis is ill-conditioned\n");
}
else
xassert(ret != ret);
if (ret != 0) goto done;
}
if (parm->meth == GLP_PRIMAL)
ret = spx_primal(P, parm);
else if (parm->meth == GLP_DUALP)
{ ret = spx_dual(P, parm);
if (ret == GLP_EFAIL && P->valid)
ret = spx_primal(P, parm);
}
else if (parm->meth == GLP_DUAL)
ret = spx_dual(P, parm);
else
xassert(parm != parm);
done: return ret;
}
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;
}
int lpx_print_sens_bnds(LPX *lp, const char *fname)
{ /* write bounds sensitivity information */
if (glp_get_status(lp) == GLP_OPT && !glp_bf_exists(lp))
glp_factorize(lp);
return glp_print_ranges(lp, 0, NULL, 0, fname);
}
static PyObject* LPX_write(LPXObject *self, PyObject *args, PyObject *keywds)
{
static char* kwlist[] = {"mps", "freemps", "prob", "sol", "sens_bnds",
"ips", "mip", NULL};
char* fnames[] = {NULL,NULL,NULL,NULL,NULL,NULL,NULL};
char* fname;
const char* err_msg = "writer for '%s' failed to write to '%s'";
int rv;
rv = PyArg_ParseTupleAndKeywords(args, keywds, "|sssssss", kwlist,
fnames,fnames+1,fnames+2,fnames+3, fnames+4,fnames+5,fnames+6);
if (!rv)
return NULL;
fname = fnames[0];
if (fname != NULL) {
rv = glp_write_mps(LP, GLP_MPS_DECK, NULL, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[0], fname);
return NULL;
}
}
fname = fnames[1];
if (fname != NULL) {
rv = glp_write_mps(LP, GLP_MPS_FILE, NULL, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[1], fname);
return NULL;
}
}
fname = fnames[2];
if (fname != NULL) {
rv = glp_write_lp(LP, NULL, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[2], fname);
return NULL;
}
}
fname = fnames[3];
if (fname != NULL) {
rv = glp_print_sol(LP, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[3], fname);
return NULL;
}
}
fname = fnames[4];
if (fname != NULL) {
if (glp_get_status(LP) == GLP_OPT && !glp_bf_exists(LP))
glp_factorize(LP);
rv = glp_print_ranges(LP, 0, NULL, 0, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[4], fname);
return NULL;
}
}
fname = fnames[5];
if (fname != NULL) {
rv = glp_print_ipt(LP, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[5], fname);
return NULL;
}
}
fname = fnames[6];
if (fname != NULL) {
glp_print_mip(LP, fname);
if (rv != 0) {
PyErr_Format(PyExc_RuntimeError, err_msg, kwlist[6], fname);
return NULL;
}
}
Py_RETURN_NONE;
}
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_warm_up(LPX *lp)
{ int m, n, j, k, ret, type, stat, p_stat, d_stat;
double lb, ub, prim, dual, tol_bnd, tol_dj, dir;
double *row_prim, *row_dual, *col_prim, *col_dual, sum;
m = lpx_get_num_rows(lp);
n = lpx_get_num_cols(lp);
/* reinvert the basis matrix, if necessary */
if (lpx_is_b_avail(lp))
ret = LPX_E_OK;
else
{ if (m == 0 || n == 0)
{ ret = LPX_E_EMPTY;
goto done;
}
#if 0
ret = lpx_invert(lp);
switch (ret)
{ case 0:
ret = LPX_E_OK;
break;
case 1:
case 2:
ret = LPX_E_SING;
goto done;
case 3:
ret = LPX_E_BADB;
goto done;
default:
xassert(ret != ret);
}
#else
switch (glp_factorize(lp))
{ case 0:
ret = LPX_E_OK;
break;
case GLP_EBADB:
ret = LPX_E_BADB;
goto done;
case GLP_ESING:
case GLP_ECOND:
ret = LPX_E_SING;
goto done;
default:
xassert(lp != lp);
}
#endif
}
/* allocate working arrays */
row_prim = xcalloc(1+m, sizeof(double));
row_dual = xcalloc(1+m, sizeof(double));
col_prim = xcalloc(1+n, sizeof(double));
col_dual = xcalloc(1+n, sizeof(double));
/* compute primal basic solution components */
lpx_eval_b_prim(lp, row_prim, col_prim);
/* determine primal status of basic solution */
tol_bnd = 3.0 * lpx_get_real_parm(lp, LPX_K_TOLBND);
p_stat = LPX_P_FEAS;
for (k = 1; k <= m+n; k++)
{ if (k <= m)
{ type = lpx_get_row_type(lp, k);
lb = lpx_get_row_lb(lp, k);
ub = lpx_get_row_ub(lp, k);
prim = row_prim[k];
}
else
{ type = lpx_get_col_type(lp, k-m);
lb = lpx_get_col_lb(lp, k-m);
ub = lpx_get_col_ub(lp, k-m);
prim = col_prim[k-m];
}
if (type == LPX_LO || type == LPX_DB || type == LPX_FX)
{ /* variable x[k] has lower bound */
if (prim < lb - tol_bnd * (1.0 + fabs(lb)))
{ p_stat = LPX_P_INFEAS;
break;
}
}
if (type == LPX_UP || type == LPX_DB || type == LPX_FX)
{ /* variable x[k] has upper bound */
if (prim > ub + tol_bnd * (1.0 + fabs(ub)))
{ p_stat = LPX_P_INFEAS;
break;
}
}
}
/* compute dual basic solution components */
lpx_eval_b_dual(lp, row_dual, col_dual);
/* determine dual status of basic solution */
tol_dj = 3.0 * lpx_get_real_parm(lp, LPX_K_TOLDJ);
dir = (lpx_get_obj_dir(lp) == LPX_MIN ? +1.0 : -1.0);
d_stat = LPX_D_FEAS;
for (k = 1; k <= m+n; k++)
{ if (k <= m)
{ stat = lpx_get_row_stat(lp, k);
dual = row_dual[k];
}
else
{ stat = lpx_get_col_stat(lp, k-m);
dual = col_dual[k-m];
}
if (stat == LPX_BS || stat == LPX_NL || stat == LPX_NF)
{ /* reduced cost of x[k] must be non-negative (minimization)
or non-positive (maximization) */
if (dir * dual < - tol_dj)
{ d_stat = LPX_D_INFEAS;
break;
}
}
if (stat == LPX_BS || stat == LPX_NU || stat == LPX_NF)
{ /* reduced cost of x[k] must be non-positive (minimization)
or non-negative (maximization) */
if (dir * dual > + tol_dj)
{ d_stat = LPX_D_INFEAS;
break;
}
}
}
/* store basic solution components */
p_stat = p_stat - LPX_P_UNDEF + GLP_UNDEF;
d_stat = d_stat - LPX_D_UNDEF + GLP_UNDEF;
sum = lpx_get_obj_coef(lp, 0);
for (j = 1; j <= n; j++)
sum += lpx_get_obj_coef(lp, j) * col_prim[j];
glp_put_solution(lp, 0, &p_stat, &d_stat, &sum,
NULL, row_prim, row_dual, NULL, col_prim, col_dual);
xassert(lpx_is_b_avail(lp));
/* free working arrays */
xfree(row_prim);
xfree(row_dual);
xfree(col_prim);
xfree(col_dual);
done: /* return to the calling program */
return ret;
}
