/* 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 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 "glpios.h"

 #include "glpnpp.h"

 #include "glpspx.h"

 /***********************************************************************

 *  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;

       parm->tol_piv = 1e-10;

       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;

 }

 /* eof */