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tempest/resources/3rdparty/glpk-4.57/src/glpapi06.c

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/* glpapi06.c (simplex method routines) */
/***********************************************************************
* This code is part of GLPK (GNU Linear Programming Kit).
*
* Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
* 2009, 2010, 2011, 2013 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 "glpios.h"
#include "glpnpp.h"
#if 0 /* 07/XI-2015 */
#include "glpspx.h"
#else
#include "simplex.h"
#define spx_dual spy_dual
#endif
/***********************************************************************
* NAME
*
* glp_simplex - solve LP problem with the simplex method
*
* SYNOPSIS
*
* int glp_simplex(glp_prob *P, const glp_smcp *parm);
*
* DESCRIPTION
*
* The routine glp_simplex is a driver to the LP solver based on the
* simplex method. This routine retrieves problem data from the
* specified problem object, calls the solver to solve the problem
* instance, and stores results of computations back into the problem
* object.
*
* The simplex solver has a set of control parameters. Values of the
* control parameters can be passed in a structure glp_smcp, which the
* parameter parm points to.
*
* The parameter parm can be specified as NULL, in which case the LP
* solver uses default settings.
*
* RETURNS
*
* 0 The LP 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_EBADB
* Unable to start the search, because the initial basis specified
* in the problem object is invalid--the number of basic (auxiliary
* and structural) variables is not the same as the number of rows in
* the problem object.
*
* GLP_ESING
* Unable to start the search, because the basis matrix correspodning
* to the initial basis is singular within the working precision.
*
* GLP_ECOND
* Unable to start the search, because the basis matrix correspodning
* to the initial basis is ill-conditioned, i.e. its condition number
* is too large.
*
* GLP_EBOUND
* Unable to start the search, because some double-bounded variables
* have incorrect bounds.
*
* GLP_EFAIL
* The search was prematurely terminated due to the solver failure.
*
* GLP_EOBJLL
* The search was prematurely terminated, because the objective
* function being maximized has reached its lower limit and continues
* decreasing (dual simplex only).
*
* GLP_EOBJUL
* The search was prematurely terminated, because the objective
* function being minimized has reached its upper limit and continues
* increasing (dual simplex only).
*
* GLP_EITLIM
* The search was prematurely terminated, because the simplex
* iteration limit has been exceeded.
*
* GLP_ETMLIM
* The search was prematurely terminated, because the time limit has
* been exceeded.
*
* GLP_ENOPFS
* The LP problem instance has no primal feasible solution (only if
* the LP presolver is used).
*
* GLP_ENODFS
* The LP problem instance has no dual feasible solution (only if the
* LP presolver is used). */
static void trivial_lp(glp_prob *P, const glp_smcp *parm)
{ /* solve trivial LP which has empty constraint matrix */
GLPROW *row;
GLPCOL *col;
int i, j;
double p_infeas, d_infeas, zeta;
P->valid = 0;
P->pbs_stat = P->dbs_stat = GLP_FEAS;
P->obj_val = P->c0;
P->some = 0;
p_infeas = d_infeas = 0.0;
/* make all auxiliary variables basic */
for (i = 1; i <= P->m; i++)
{ row = P->row[i];
row->stat = GLP_BS;
row->prim = row->dual = 0.0;
/* check primal feasibility */
if (row->type == GLP_LO || row->type == GLP_DB ||
row->type == GLP_FX)
{ /* row has lower bound */
if (row->lb > + parm->tol_bnd)
{ P->pbs_stat = GLP_NOFEAS;
if (P->some == 0 && parm->meth != GLP_PRIMAL)
P->some = i;
}
if (p_infeas < + row->lb)
p_infeas = + row->lb;
}
if (row->type == GLP_UP || row->type == GLP_DB ||
row->type == GLP_FX)
{ /* row has upper bound */
if (row->ub < - parm->tol_bnd)
{ P->pbs_stat = GLP_NOFEAS;
if (P->some == 0 && parm->meth != GLP_PRIMAL)
P->some = i;
}
if (p_infeas < - row->ub)
p_infeas = - row->ub;
}
}
/* determine scale factor for the objective row */
zeta = 1.0;
for (j = 1; j <= P->n; j++)
{ col = P->col[j];
if (zeta < fabs(col->coef)) zeta = fabs(col->coef);
}
zeta = (P->dir == GLP_MIN ? +1.0 : -1.0) / zeta;
/* make all structural variables non-basic */
for (j = 1; j <= P->n; j++)
{ col = P->col[j];
if (col->type == GLP_FR)
col->stat = GLP_NF, col->prim = 0.0;
else if (col->type == GLP_LO)
lo: col->stat = GLP_NL, col->prim = col->lb;
else if (col->type == GLP_UP)
up: col->stat = GLP_NU, col->prim = col->ub;
else if (col->type == GLP_DB)
{ if (zeta * col->coef > 0.0)
goto lo;
else if (zeta * col->coef < 0.0)
goto up;
else if (fabs(col->lb) <= fabs(col->ub))
goto lo;
else
goto up;
}
else if (col->type == GLP_FX)
col->stat = GLP_NS, col->prim = col->lb;
col->dual = col->coef;
P->obj_val += col->coef * col->prim;
/* check dual feasibility */
if (col->type == GLP_FR || col->type == GLP_LO)
{ /* column has no upper bound */
if (zeta * col->dual < - parm->tol_dj)
{ P->dbs_stat = GLP_NOFEAS;
if (P->some == 0 && parm->meth == GLP_PRIMAL)
P->some = P->m + j;
}
if (d_infeas < - zeta * col->dual)
d_infeas = - zeta * col->dual;
}
if (col->type == GLP_FR || col->type == GLP_UP)
{ /* column has no lower bound */
if (zeta * col->dual > + parm->tol_dj)
{ P->dbs_stat = GLP_NOFEAS;
if (P->some == 0 && parm->meth == GLP_PRIMAL)
P->some = P->m + j;
}
if (d_infeas < + zeta * col->dual)
d_infeas = + zeta * col->dual;
}
}
/* simulate the simplex solver output */
if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0)
{ xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt,
P->obj_val, parm->meth == GLP_PRIMAL ? p_infeas : d_infeas);
}
if (parm->msg_lev >= GLP_MSG_ALL && parm->out_dly == 0)
{ if (P->pbs_stat == GLP_FEAS && P->dbs_stat == GLP_FEAS)
xprintf("OPTIMAL SOLUTION FOUND\n");
else if (P->pbs_stat == GLP_NOFEAS)
xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n");
else if (parm->meth == GLP_PRIMAL)
xprintf("PROBLEM HAS UNBOUNDED SOLUTION\n");
else
xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n");
}
return;
}
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 int preprocess_and_solve_lp(glp_prob *P, const glp_smcp *parm)
{ /* solve LP using the preprocessor */
NPP *npp;
glp_prob *lp = NULL;
glp_bfcp bfcp;
int ret;
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("Preprocessing...\n");
/* create preprocessor workspace */
npp = npp_create_wksp();
/* load original problem into the preprocessor workspace */
npp_load_prob(npp, P, GLP_OFF, GLP_SOL, GLP_OFF);
/* process LP prior to applying primal/dual simplex method */
ret = npp_simplex(npp, parm);
if (ret == 0)
;
else if (ret == GLP_ENOPFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n");
}
else if (ret == GLP_ENODFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n");
}
else
xassert(ret != ret);
if (ret != 0) goto done;
/* build transformed LP */
lp = glp_create_prob();
npp_build_prob(npp, lp);
/* if the transformed LP is empty, it has empty solution, which
is optimal */
if (lp->m == 0 && lp->n == 0)
{ lp->pbs_stat = lp->dbs_stat = GLP_FEAS;
lp->obj_val = lp->c0;
if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0)
{ xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt,
lp->obj_val, 0.0);
}
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("OPTIMAL SOLUTION FOUND BY LP PREPROCESSOR\n");
goto post;
}
if (parm->msg_lev >= GLP_MSG_ALL)
{ xprintf("%d row%s, %d column%s, %d non-zero%s\n",
lp->m, lp->m == 1 ? "" : "s", lp->n, lp->n == 1 ? "" : "s",
lp->nnz, lp->nnz == 1 ? "" : "s");
}
/* inherit basis factorization control parameters */
glp_get_bfcp(P, &bfcp);
glp_set_bfcp(lp, &bfcp);
/* scale the transformed problem */
{ ENV *env = get_env_ptr();
int term_out = env->term_out;
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_scale_prob(lp, GLP_SF_AUTO);
env->term_out = term_out;
}
/* build advanced initial basis */
{ ENV *env = get_env_ptr();
int term_out = env->term_out;
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_adv_basis(lp, 0);
env->term_out = term_out;
}
/* solve the transformed LP */
lp->it_cnt = P->it_cnt;
ret = solve_lp(lp, parm);
P->it_cnt = lp->it_cnt;
/* only optimal solution can be postprocessed */
if (!(ret == 0 && lp->pbs_stat == GLP_FEAS && lp->dbs_stat ==
GLP_FEAS))
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: unable to recover undefined or non-op"
"timal solution\n");
if (ret == 0)
{ if (lp->pbs_stat == GLP_NOFEAS)
ret = GLP_ENOPFS;
else if (lp->dbs_stat == GLP_NOFEAS)
ret = GLP_ENODFS;
else
xassert(lp != lp);
}
goto done;
}
post: /* postprocess solution from the transformed LP */
npp_postprocess(npp, lp);
/* the transformed LP is no longer needed */
glp_delete_prob(lp), lp = NULL;
/* store solution to the original problem */
npp_unload_sol(npp, P);
/* the original LP has been successfully solved */
ret = 0;
done: /* delete the transformed LP, if it exists */
if (lp != NULL) glp_delete_prob(lp);
/* delete preprocessor workspace */
npp_delete_wksp(npp);
return ret;
}
int glp_simplex(glp_prob *P, const glp_smcp *parm)
{ /* solve LP problem with the simplex method */
glp_smcp _parm;
int i, j, ret;
/* check problem object */
if (P == NULL || P->magic != GLP_PROB_MAGIC)
xerror("glp_simplex: P = %p; invalid problem object\n", P);
if (P->tree != NULL && P->tree->reason != 0)
xerror("glp_simplex: operation not allowed\n");
/* check control parameters */
if (parm == NULL)
parm = &_parm, glp_init_smcp((glp_smcp *)parm);
if (!(parm->msg_lev == GLP_MSG_OFF ||
parm->msg_lev == GLP_MSG_ERR ||
parm->msg_lev == GLP_MSG_ON ||
parm->msg_lev == GLP_MSG_ALL ||
parm->msg_lev == GLP_MSG_DBG))
xerror("glp_simplex: msg_lev = %d; invalid parameter\n",
parm->msg_lev);
if (!(parm->meth == GLP_PRIMAL ||
parm->meth == GLP_DUALP ||
parm->meth == GLP_DUAL))
xerror("glp_simplex: meth = %d; invalid parameter\n",
parm->meth);
if (!(parm->pricing == GLP_PT_STD ||
parm->pricing == GLP_PT_PSE))
xerror("glp_simplex: pricing = %d; invalid parameter\n",
parm->pricing);
if (!(parm->r_test == GLP_RT_STD ||
parm->r_test == GLP_RT_HAR))
xerror("glp_simplex: r_test = %d; invalid parameter\n",
parm->r_test);
if (!(0.0 < parm->tol_bnd && parm->tol_bnd < 1.0))
xerror("glp_simplex: tol_bnd = %g; invalid parameter\n",
parm->tol_bnd);
if (!(0.0 < parm->tol_dj && parm->tol_dj < 1.0))
xerror("glp_simplex: tol_dj = %g; invalid parameter\n",
parm->tol_dj);
if (!(0.0 < parm->tol_piv && parm->tol_piv < 1.0))
xerror("glp_simplex: tol_piv = %g; invalid parameter\n",
parm->tol_piv);
if (parm->it_lim < 0)
xerror("glp_simplex: it_lim = %d; invalid parameter\n",
parm->it_lim);
if (parm->tm_lim < 0)
xerror("glp_simplex: tm_lim = %d; invalid parameter\n",
parm->tm_lim);
if (parm->out_frq < 1)
xerror("glp_simplex: out_frq = %d; invalid parameter\n",
parm->out_frq);
if (parm->out_dly < 0)
xerror("glp_simplex: out_dly = %d; invalid parameter\n",
parm->out_dly);
if (!(parm->presolve == GLP_ON || parm->presolve == GLP_OFF))
xerror("glp_simplex: presolve = %d; invalid parameter\n",
parm->presolve);
/* basic solution is currently undefined */
P->pbs_stat = P->dbs_stat = GLP_UNDEF;
P->obj_val = 0.0;
P->some = 0;
/* check bounds of double-bounded variables */
for (i = 1; i <= P->m; i++)
{ GLPROW *row = P->row[i];
if (row->type == GLP_DB && row->lb >= row->ub)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: row %d: lb = %g, ub = %g; incorrec"
"t bounds\n", i, row->lb, row->ub);
ret = GLP_EBOUND;
goto done;
}
}
for (j = 1; j <= P->n; j++)
{ GLPCOL *col = P->col[j];
if (col->type == GLP_DB && col->lb >= col->ub)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: column %d: lb = %g, ub = %g; incor"
"rect bounds\n", j, col->lb, col->ub);
ret = GLP_EBOUND;
goto done;
}
}
/* solve LP problem */
if (parm->msg_lev >= GLP_MSG_ALL)
{ xprintf("GLPK Simplex Optimizer, v%s\n", glp_version());
xprintf("%d row%s, %d column%s, %d non-zero%s\n",
P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s",
P->nnz, P->nnz == 1 ? "" : "s");
}
if (P->nnz == 0)
trivial_lp(P, parm), ret = 0;
else if (!parm->presolve)
ret = solve_lp(P, parm);
else
ret = preprocess_and_solve_lp(P, parm);
done: /* return to the application program */
return ret;
}
/***********************************************************************
* NAME
*
* glp_init_smcp - initialize simplex method control parameters
*
* SYNOPSIS
*
* void glp_init_smcp(glp_smcp *parm);
*
* DESCRIPTION
*
* The routine glp_init_smcp initializes control parameters, which are
* used by the simplex solver, with default values.
*
* Default values of the control parameters are stored in a glp_smcp
* structure, which the parameter parm points to. */
void glp_init_smcp(glp_smcp *parm)
{ parm->msg_lev = GLP_MSG_ALL;
parm->meth = GLP_PRIMAL;
parm->pricing = GLP_PT_PSE;
parm->r_test = GLP_RT_HAR;
parm->tol_bnd = 1e-7;
parm->tol_dj = 1e-7;
#if 0 /* 07/XI-2015 */
parm->tol_piv = 1e-10;
#else
parm->tol_piv = 1e-9;
#endif
parm->obj_ll = -DBL_MAX;
parm->obj_ul = +DBL_MAX;
parm->it_lim = INT_MAX;
parm->tm_lim = INT_MAX;
parm->out_frq = 500;
parm->out_dly = 0;
parm->presolve = GLP_OFF;
return;
}
/***********************************************************************
* NAME
*
* glp_get_status - retrieve generic status of basic solution
*
* SYNOPSIS
*
* int glp_get_status(glp_prob *lp);
*
* RETURNS
*
* The routine glp_get_status reports the generic status of the basic
* solution for the specified problem object as follows:
*
* GLP_OPT - solution is optimal;
* GLP_FEAS - solution is feasible;
* GLP_INFEAS - solution is infeasible;
* GLP_NOFEAS - problem has no feasible solution;
* GLP_UNBND - problem has unbounded solution;
* GLP_UNDEF - solution is undefined. */
int glp_get_status(glp_prob *lp)
{ int status;
status = glp_get_prim_stat(lp);
switch (status)
{ case GLP_FEAS:
switch (glp_get_dual_stat(lp))
{ case GLP_FEAS:
status = GLP_OPT;
break;
case GLP_NOFEAS:
status = GLP_UNBND;
break;
case GLP_UNDEF:
case GLP_INFEAS:
status = status;
break;
default:
xassert(lp != lp);
}
break;
case GLP_UNDEF:
case GLP_INFEAS:
case GLP_NOFEAS:
status = status;
break;
default:
xassert(lp != lp);
}
return status;
}
/***********************************************************************
* NAME
*
* glp_get_prim_stat - retrieve status of primal basic solution
*
* SYNOPSIS
*
* int glp_get_prim_stat(glp_prob *lp);
*
* RETURNS
*
* The routine glp_get_prim_stat reports the status of the primal basic
* solution for the specified problem object as follows:
*
* GLP_UNDEF - primal solution is undefined;
* GLP_FEAS - primal solution is feasible;
* GLP_INFEAS - primal solution is infeasible;
* GLP_NOFEAS - no primal feasible solution exists. */
int glp_get_prim_stat(glp_prob *lp)
{ int pbs_stat = lp->pbs_stat;
return pbs_stat;
}
/***********************************************************************
* NAME
*
* glp_get_dual_stat - retrieve status of dual basic solution
*
* SYNOPSIS
*
* int glp_get_dual_stat(glp_prob *lp);
*
* RETURNS
*
* The routine glp_get_dual_stat reports the status of the dual basic
* solution for the specified problem object as follows:
*
* GLP_UNDEF - dual solution is undefined;
* GLP_FEAS - dual solution is feasible;
* GLP_INFEAS - dual solution is infeasible;
* GLP_NOFEAS - no dual feasible solution exists. */
int glp_get_dual_stat(glp_prob *lp)
{ int dbs_stat = lp->dbs_stat;
return dbs_stat;
}
/***********************************************************************
* NAME
*
* glp_get_obj_val - retrieve objective value (basic solution)
*
* SYNOPSIS
*
* double glp_get_obj_val(glp_prob *lp);
*
* RETURNS
*
* The routine glp_get_obj_val returns value of the objective function
* for basic solution. */
double glp_get_obj_val(glp_prob *lp)
{ /*struct LPXCPS *cps = lp->cps;*/
double z;
z = lp->obj_val;
/*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/
return z;
}
/***********************************************************************
* NAME
*
* glp_get_row_stat - retrieve row status
*
* SYNOPSIS
*
* int glp_get_row_stat(glp_prob *lp, int i);
*
* RETURNS
*
* The routine glp_get_row_stat returns current status assigned to the
* auxiliary variable associated with i-th row as follows:
*
* GLP_BS - basic variable;
* GLP_NL - non-basic variable on its lower bound;
* GLP_NU - non-basic variable on its upper bound;
* GLP_NF - non-basic free (unbounded) variable;
* GLP_NS - non-basic fixed variable. */
int glp_get_row_stat(glp_prob *lp, int i)
{ if (!(1 <= i && i <= lp->m))
xerror("glp_get_row_stat: i = %d; row number out of range\n",
i);
return lp->row[i]->stat;
}
/***********************************************************************
* NAME
*
* glp_get_row_prim - retrieve row primal value (basic solution)
*
* SYNOPSIS
*
* double glp_get_row_prim(glp_prob *lp, int i);
*
* RETURNS
*
* The routine glp_get_row_prim returns primal value of the auxiliary
* variable associated with i-th row. */
double glp_get_row_prim(glp_prob *lp, int i)
{ /*struct LPXCPS *cps = lp->cps;*/
double prim;
if (!(1 <= i && i <= lp->m))
xerror("glp_get_row_prim: i = %d; row number out of range\n",
i);
prim = lp->row[i]->prim;
/*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/
return prim;
}
/***********************************************************************
* NAME
*
* glp_get_row_dual - retrieve row dual value (basic solution)
*
* SYNOPSIS
*
* double glp_get_row_dual(glp_prob *lp, int i);
*
* RETURNS
*
* The routine glp_get_row_dual returns dual value (i.e. reduced cost)
* of the auxiliary variable associated with i-th row. */
double glp_get_row_dual(glp_prob *lp, int i)
{ /*struct LPXCPS *cps = lp->cps;*/
double dual;
if (!(1 <= i && i <= lp->m))
xerror("glp_get_row_dual: i = %d; row number out of range\n",
i);
dual = lp->row[i]->dual;
/*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/
return dual;
}
/***********************************************************************
* NAME
*
* glp_get_col_stat - retrieve column status
*
* SYNOPSIS
*
* int glp_get_col_stat(glp_prob *lp, int j);
*
* RETURNS
*
* The routine glp_get_col_stat returns current status assigned to the
* structural variable associated with j-th column as follows:
*
* GLP_BS - basic variable;
* GLP_NL - non-basic variable on its lower bound;
* GLP_NU - non-basic variable on its upper bound;
* GLP_NF - non-basic free (unbounded) variable;
* GLP_NS - non-basic fixed variable. */
int glp_get_col_stat(glp_prob *lp, int j)
{ if (!(1 <= j && j <= lp->n))
xerror("glp_get_col_stat: j = %d; column number out of range\n"
, j);
return lp->col[j]->stat;
}
/***********************************************************************
* NAME
*
* glp_get_col_prim - retrieve column primal value (basic solution)
*
* SYNOPSIS
*
* double glp_get_col_prim(glp_prob *lp, int j);
*
* RETURNS
*
* The routine glp_get_col_prim returns primal value of the structural
* variable associated with j-th column. */
double glp_get_col_prim(glp_prob *lp, int j)
{ /*struct LPXCPS *cps = lp->cps;*/
double prim;
if (!(1 <= j && j <= lp->n))
xerror("glp_get_col_prim: j = %d; column number out of range\n"
, j);
prim = lp->col[j]->prim;
/*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/
return prim;
}
/***********************************************************************
* NAME
*
* glp_get_col_dual - retrieve column dual value (basic solution)
*
* SYNOPSIS
*
* double glp_get_col_dual(glp_prob *lp, int j);
*
* RETURNS
*
* The routine glp_get_col_dual returns dual value (i.e. reduced cost)
* of the structural variable associated with j-th column. */
double glp_get_col_dual(glp_prob *lp, int j)
{ /*struct LPXCPS *cps = lp->cps;*/
double dual;
if (!(1 <= j && j <= lp->n))
xerror("glp_get_col_dual: j = %d; column number out of range\n"
, j);
dual = lp->col[j]->dual;
/*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/
return dual;
}
/***********************************************************************
* NAME
*
* glp_get_unbnd_ray - determine variable causing unboundedness
*
* SYNOPSIS
*
* int glp_get_unbnd_ray(glp_prob *lp);
*
* RETURNS
*
* The routine glp_get_unbnd_ray returns the number k of a variable,
* which causes primal or dual unboundedness. If 1 <= k <= m, it is
* k-th auxiliary variable, and if m+1 <= k <= m+n, it is (k-m)-th
* structural variable, where m is the number of rows, n is the number
* of columns in the problem object. If such variable is not defined,
* the routine returns 0.
*
* COMMENTS
*
* If it is not exactly known which version of the simplex solver
* detected unboundedness, i.e. whether the unboundedness is primal or
* dual, it is sufficient to check the status of the variable reported
* with the routine glp_get_row_stat or glp_get_col_stat. If the
* variable is non-basic, the unboundedness is primal, otherwise, if
* the variable is basic, the unboundedness is dual (the latter case
* means that the problem has no primal feasible dolution). */
int glp_get_unbnd_ray(glp_prob *lp)
{ int k;
k = lp->some;
xassert(k >= 0);
if (k > lp->m + lp->n) k = 0;
return k;
}
#if 1 /* 08/VIII-2013 */
int glp_get_it_cnt(glp_prob *P)
{ /* get simplex solver iteration count */
return P->it_cnt;
}
#endif
#if 1 /* 08/VIII-2013 */
void glp_set_it_cnt(glp_prob *P, int it_cnt)
{ /* set simplex solver iteration count */
P->it_cnt = it_cnt;
return;
}
#endif
/* eof */