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+/* glpapi08.c (interior-point 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 "glpipm.h"
+#include "npp.h"
+
+/***********************************************************************
+* NAME
+*
+* glp_interior - solve LP problem with the interior-point method
+*
+* SYNOPSIS
+*
+* int glp_interior(glp_prob *P, const glp_iptcp *parm);
+*
+* The routine glp_interior is a driver to the LP solver based on the
+* interior-point method.
+*
+* The interior-point solver has a set of control parameters. Values of
+* the control parameters can be passed in a structure glp_iptcp, which
+* the parameter parm points to.
+*
+* Currently this routine implements an easy variant of the primal-dual
+* interior-point method based on Mehrotra's technique.
+*
+* This routine transforms the original LP problem to an equivalent LP
+* problem in the standard formulation (all constraints are equalities,
+* all variables are non-negative), calls the routine ipm_main to solve
+* the transformed problem, and then transforms an obtained solution to
+* the solution of the original problem.
+*
+* 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_EFAIL
+* The problem has no rows/columns.
+*
+* GLP_ENOCVG
+* Very slow convergence or divergence.
+*
+* GLP_EITLIM
+* Iteration limit exceeded.
+*
+* GLP_EINSTAB
+* Numerical instability on solving Newtonian system. */
+
+static void transform(NPP *npp)
+{ /* transform LP to the standard formulation */
+ NPPROW *row, *prev_row;
+ NPPCOL *col, *prev_col;
+ for (row = npp->r_tail; row != NULL; row = prev_row)
+ { prev_row = row->prev;
+ if (row->lb == -DBL_MAX && row->ub == +DBL_MAX)
+ npp_free_row(npp, row);
+ else if (row->lb == -DBL_MAX)
+ npp_leq_row(npp, row);
+ else if (row->ub == +DBL_MAX)
+ npp_geq_row(npp, row);
+ else if (row->lb != row->ub)
+ { if (fabs(row->lb) < fabs(row->ub))
+ npp_geq_row(npp, row);
+ else
+ npp_leq_row(npp, row);
+ }
+ }
+ for (col = npp->c_tail; col != NULL; col = prev_col)
+ { prev_col = col->prev;
+ if (col->lb == -DBL_MAX && col->ub == +DBL_MAX)
+ npp_free_col(npp, col);
+ else if (col->lb == -DBL_MAX)
+ npp_ubnd_col(npp, col);
+ else if (col->ub == +DBL_MAX)
+ { if (col->lb != 0.0)
+ npp_lbnd_col(npp, col);
+ }
+ else if (col->lb != col->ub)
+ { if (fabs(col->lb) < fabs(col->ub))
+ { if (col->lb != 0.0)
+ npp_lbnd_col(npp, col);
+ }
+ else
+ npp_ubnd_col(npp, col);
+ npp_dbnd_col(npp, col);
+ }
+ else
+ npp_fixed_col(npp, col);
+ }
+ for (row = npp->r_head; row != NULL; row = row->next)
+ xassert(row->lb == row->ub);
+ for (col = npp->c_head; col != NULL; col = col->next)
+ xassert(col->lb == 0.0 && col->ub == +DBL_MAX);
+ return;
+}
+
+int glp_interior(glp_prob *P, const glp_iptcp *parm)
+{ glp_iptcp _parm;
+ GLPROW *row;
+ GLPCOL *col;
+ NPP *npp = NULL;
+ glp_prob *prob = NULL;
+ int i, j, ret;
+ /* check control parameters */
+ if (parm == NULL)
+ glp_init_iptcp(&_parm), parm = &_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))
+ xerror("glp_interior: msg_lev = %d; invalid parameter\n",
+ parm->msg_lev);
+ if (!(parm->ord_alg == GLP_ORD_NONE ||
+ parm->ord_alg == GLP_ORD_QMD ||
+ parm->ord_alg == GLP_ORD_AMD ||
+ parm->ord_alg == GLP_ORD_SYMAMD))
+ xerror("glp_interior: ord_alg = %d; invalid parameter\n",
+ parm->ord_alg);
+ /* interior-point solution is currently undefined */
+ P->ipt_stat = GLP_UNDEF;
+ P->ipt_obj = 0.0;
+ /* check bounds of double-bounded variables */
+ for (i = 1; i <= P->m; i++)
+ { row = P->row[i];
+ if (row->type == GLP_DB && row->lb >= row->ub)
+ { if (parm->msg_lev >= GLP_MSG_ERR)
+ xprintf("glp_interior: row %d: lb = %g, ub = %g; incorre"
+ "ct bounds\n", i, row->lb, row->ub);
+ ret = GLP_EBOUND;
+ goto done;
+ }
+ }
+ for (j = 1; j <= P->n; j++)
+ { col = P->col[j];
+ if (col->type == GLP_DB && col->lb >= col->ub)
+ { if (parm->msg_lev >= GLP_MSG_ERR)
+ xprintf("glp_interior: column %d: lb = %g, ub = %g; inco"
+ "rrect bounds\n", j, col->lb, col->ub);
+ ret = GLP_EBOUND;
+ goto done;
+ }
+ }
+ /* transform LP to the standard formulation */
+ if (parm->msg_lev >= GLP_MSG_ALL)
+ xprintf("Original LP has %d row(s), %d column(s), and %d non-z"
+ "ero(s)\n", P->m, P->n, P->nnz);
+ npp = npp_create_wksp();
+ npp_load_prob(npp, P, GLP_OFF, GLP_IPT, GLP_ON);
+ transform(npp);
+ prob = glp_create_prob();
+ npp_build_prob(npp, prob);
+ if (parm->msg_lev >= GLP_MSG_ALL)
+ xprintf("Working LP has %d row(s), %d column(s), and %d non-ze"
+ "ro(s)\n", prob->m, prob->n, prob->nnz);
+#if 1
+ /* currently empty problem cannot be solved */
+ if (!(prob->m > 0 && prob->n > 0))
+ { if (parm->msg_lev >= GLP_MSG_ERR)
+ xprintf("glp_interior: unable to solve empty problem\n");
+ ret = GLP_EFAIL;
+ goto done;
+ }
+#endif
+ /* scale the resultant LP */
+ { ENV *env = get_env_ptr();
+ int term_out = env->term_out;
+ env->term_out = GLP_OFF;
+ glp_scale_prob(prob, GLP_SF_EQ);
+ env->term_out = term_out;
+ }
+ /* warn about dense columns */
+ if (parm->msg_lev >= GLP_MSG_ON && prob->m >= 200)
+ { int len, cnt = 0;
+ for (j = 1; j <= prob->n; j++)
+ { len = glp_get_mat_col(prob, j, NULL, NULL);
+ if ((double)len >= 0.20 * (double)prob->m) cnt++;
+ }
+ if (cnt == 1)
+ xprintf("WARNING: PROBLEM HAS ONE DENSE COLUMN\n");
+ else if (cnt > 0)
+ xprintf("WARNING: PROBLEM HAS %d DENSE COLUMNS\n", cnt);
+ }
+ /* solve the transformed LP */
+ ret = ipm_solve(prob, parm);
+ /* postprocess solution from the transformed LP */
+ npp_postprocess(npp, prob);
+ /* and store solution to the original LP */
+ npp_unload_sol(npp, P);
+done: /* free working program objects */
+ if (npp != NULL) npp_delete_wksp(npp);
+ if (prob != NULL) glp_delete_prob(prob);
+ /* return to the application program */
+ return ret;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_init_iptcp - initialize interior-point solver control parameters
+*
+* SYNOPSIS
+*
+* void glp_init_iptcp(glp_iptcp *parm);
+*
+* DESCRIPTION
+*
+* The routine glp_init_iptcp initializes control parameters, which are
+* used by the interior-point solver, with default values.
+*
+* Default values of the control parameters are stored in the glp_iptcp
+* structure, which the parameter parm points to. */
+
+void glp_init_iptcp(glp_iptcp *parm)
+{ parm->msg_lev = GLP_MSG_ALL;
+ parm->ord_alg = GLP_ORD_AMD;
+ return;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_status - retrieve status of interior-point solution
+*
+* SYNOPSIS
+*
+* int glp_ipt_status(glp_prob *lp);
+*
+* RETURNS
+*
+* The routine glp_ipt_status reports the status of solution found by
+* the interior-point solver as follows:
+*
+* GLP_UNDEF - interior-point solution is undefined;
+* GLP_OPT - interior-point solution is optimal;
+* GLP_INFEAS - interior-point solution is infeasible;
+* GLP_NOFEAS - no feasible solution exists. */
+
+int glp_ipt_status(glp_prob *lp)
+{ int ipt_stat = lp->ipt_stat;
+ return ipt_stat;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_obj_val - retrieve objective value (interior point)
+*
+* SYNOPSIS
+*
+* double glp_ipt_obj_val(glp_prob *lp);
+*
+* RETURNS
+*
+* The routine glp_ipt_obj_val returns value of the objective function
+* for interior-point solution. */
+
+double glp_ipt_obj_val(glp_prob *lp)
+{ /*struct LPXCPS *cps = lp->cps;*/
+ double z;
+ z = lp->ipt_obj;
+ /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/
+ return z;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_row_prim - retrieve row primal value (interior point)
+*
+* SYNOPSIS
+*
+* double glp_ipt_row_prim(glp_prob *lp, int i);
+*
+* RETURNS
+*
+* The routine glp_ipt_row_prim returns primal value of the auxiliary
+* variable associated with i-th row. */
+
+double glp_ipt_row_prim(glp_prob *lp, int i)
+{ /*struct LPXCPS *cps = lp->cps;*/
+ double pval;
+ if (!(1 <= i && i <= lp->m))
+ xerror("glp_ipt_row_prim: i = %d; row number out of range\n",
+ i);
+ pval = lp->row[i]->pval;
+ /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/
+ return pval;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_row_dual - retrieve row dual value (interior point)
+*
+* SYNOPSIS
+*
+* double glp_ipt_row_dual(glp_prob *lp, int i);
+*
+* RETURNS
+*
+* The routine glp_ipt_row_dual returns dual value (i.e. reduced cost)
+* of the auxiliary variable associated with i-th row. */
+
+double glp_ipt_row_dual(glp_prob *lp, int i)
+{ /*struct LPXCPS *cps = lp->cps;*/
+ double dval;
+ if (!(1 <= i && i <= lp->m))
+ xerror("glp_ipt_row_dual: i = %d; row number out of range\n",
+ i);
+ dval = lp->row[i]->dval;
+ /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/
+ return dval;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_col_prim - retrieve column primal value (interior point)
+*
+* SYNOPSIS
+*
+* double glp_ipt_col_prim(glp_prob *lp, int j);
+*
+* RETURNS
+*
+* The routine glp_ipt_col_prim returns primal value of the structural
+* variable associated with j-th column. */
+
+double glp_ipt_col_prim(glp_prob *lp, int j)
+{ /*struct LPXCPS *cps = lp->cps;*/
+ double pval;
+ if (!(1 <= j && j <= lp->n))
+ xerror("glp_ipt_col_prim: j = %d; column number out of range\n"
+ , j);
+ pval = lp->col[j]->pval;
+ /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/
+ return pval;
+}
+
+/***********************************************************************
+* NAME
+*
+* glp_ipt_col_dual - retrieve column dual value (interior point)
+*
+* SYNOPSIS
+*
+* double glp_ipt_col_dual(glp_prob *lp, int j);
+*
+* RETURNS
+*
+* The routine glp_ipt_col_dual returns dual value (i.e. reduced cost)
+* of the structural variable associated with j-th column. */
+
+double glp_ipt_col_dual(glp_prob *lp, int j)
+{ /*struct LPXCPS *cps = lp->cps;*/
+ double dval;
+ if (!(1 <= j && j <= lp->n))
+ xerror("glp_ipt_col_dual: j = %d; column number out of range\n"
+ , j);
+ dval = lp->col[j]->dval;
+ /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/
+ return dval;
+}
+
+/* eof */