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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 "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
*
* 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 */