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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 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 "glpapi.h"
- #include "glpipm.h"
- #include "glpnpp.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
- *
- * #include "glplpx.h"
- * 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 */
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