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/* glpapi13.c (branch-and-bound interface 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"
/***********************************************************************
* NAME
*
* glp_ios_reason - determine reason for calling the callback routine
*
* SYNOPSIS
*
* glp_ios_reason(glp_tree *tree);
*
* RETURNS
*
* The routine glp_ios_reason returns a code, which indicates why the
* user-defined callback routine is being called. */
int glp_ios_reason(glp_tree *tree)
{ return
tree->reason;
}
/***********************************************************************
* NAME
*
* glp_ios_get_prob - access the problem object
*
* SYNOPSIS
*
* glp_prob *glp_ios_get_prob(glp_tree *tree);
*
* DESCRIPTION
*
* The routine glp_ios_get_prob can be called from the user-defined
* callback routine to access the problem object, which is used by the
* MIP solver. It is the original problem object passed to the routine
* glp_intopt if the MIP presolver is not used; otherwise it is an
* internal problem object built by the presolver. If the current
* subproblem exists, LP segment of the problem object corresponds to
* its LP relaxation.
*
* RETURNS
*
* The routine glp_ios_get_prob returns a pointer to the problem object
* used by the MIP solver. */
glp_prob *glp_ios_get_prob(glp_tree *tree)
{ return
tree->mip;
}
/***********************************************************************
* NAME
*
* glp_ios_tree_size - determine size of the branch-and-bound tree
*
* SYNOPSIS
*
* void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt,
* int *t_cnt);
*
* DESCRIPTION
*
* The routine glp_ios_tree_size stores the following three counts which
* characterize the current size of the branch-and-bound tree:
*
* a_cnt is the current number of active nodes, i.e. the current size of
* the active list;
*
* n_cnt is the current number of all (active and inactive) nodes;
*
* t_cnt is the total number of nodes including those which have been
* already removed from the tree. This count is increased whenever
* a new node appears in the tree and never decreased.
*
* If some of the parameters a_cnt, n_cnt, t_cnt is a null pointer, the
* corresponding count is not stored. */
void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt,
int *t_cnt)
{ if (a_cnt != NULL) *a_cnt = tree->a_cnt;
if (n_cnt != NULL) *n_cnt = tree->n_cnt;
if (t_cnt != NULL) *t_cnt = tree->t_cnt;
return;
}
/***********************************************************************
* NAME
*
* glp_ios_curr_node - determine current active subproblem
*
* SYNOPSIS
*
* int glp_ios_curr_node(glp_tree *tree);
*
* RETURNS
*
* The routine glp_ios_curr_node returns the reference number of the
* current active subproblem. However, if the current subproblem does
* not exist, the routine returns zero. */
int glp_ios_curr_node(glp_tree *tree)
{ IOSNPD *node;
/* obtain pointer to the current subproblem */
node = tree->curr;
/* return its reference number */
return node == NULL ? 0 : node->p;
}
/***********************************************************************
* NAME
*
* glp_ios_next_node - determine next active subproblem
*
* SYNOPSIS
*
* int glp_ios_next_node(glp_tree *tree, int p);
*
* RETURNS
*
* If the parameter p is zero, the routine glp_ios_next_node returns
* the reference number of the first active subproblem. However, if the
* tree is empty, zero is returned.
*
* If the parameter p is not zero, it must specify the reference number
* of some active subproblem, in which case the routine returns the
* reference number of the next active subproblem. However, if there is
* no next active subproblem in the list, zero is returned.
*
* All subproblems in the active list are ordered chronologically, i.e.
* subproblem A precedes subproblem B if A was created before B. */
int glp_ios_next_node(glp_tree *tree, int p)
{ IOSNPD *node;
if (p == 0)
{ /* obtain pointer to the first active subproblem */
node = tree->head;
}
else
{ /* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_next_node: p = %d; invalid subproblem refer"
"ence number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* the specified subproblem must be active */
if (node->count != 0)
xerror("glp_ios_next_node: p = %d; subproblem not in the ac"
"tive list\n", p);
/* obtain pointer to the next active subproblem */
node = node->next;
}
/* return the reference number */
return node == NULL ? 0 : node->p;
}
/***********************************************************************
* NAME
*
* glp_ios_prev_node - determine previous active subproblem
*
* SYNOPSIS
*
* int glp_ios_prev_node(glp_tree *tree, int p);
*
* RETURNS
*
* If the parameter p is zero, the routine glp_ios_prev_node returns
* the reference number of the last active subproblem. However, if the
* tree is empty, zero is returned.
*
* If the parameter p is not zero, it must specify the reference number
* of some active subproblem, in which case the routine returns the
* reference number of the previous active subproblem. However, if there
* is no previous active subproblem in the list, zero is returned.
*
* All subproblems in the active list are ordered chronologically, i.e.
* subproblem A precedes subproblem B if A was created before B. */
int glp_ios_prev_node(glp_tree *tree, int p)
{ IOSNPD *node;
if (p == 0)
{ /* obtain pointer to the last active subproblem */
node = tree->tail;
}
else
{ /* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_prev_node: p = %d; invalid subproblem refer"
"ence number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* the specified subproblem must be active */
if (node->count != 0)
xerror("glp_ios_prev_node: p = %d; subproblem not in the ac"
"tive list\n", p);
/* obtain pointer to the previous active subproblem */
node = node->prev;
}
/* return the reference number */
return node == NULL ? 0 : node->p;
}
/***********************************************************************
* NAME
*
* glp_ios_up_node - determine parent subproblem
*
* SYNOPSIS
*
* int glp_ios_up_node(glp_tree *tree, int p);
*
* RETURNS
*
* The parameter p must specify the reference number of some (active or
* inactive) subproblem, in which case the routine iet_get_up_node
* returns the reference number of its parent subproblem. However, if
* the specified subproblem is the root of the tree and, therefore, has
* no parent, the routine returns zero. */
int glp_ios_up_node(glp_tree *tree, int p)
{ IOSNPD *node;
/* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_up_node: p = %d; invalid subproblem reference "
"number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* obtain pointer to the parent subproblem */
node = node->up;
/* return the reference number */
return node == NULL ? 0 : node->p;
}
/***********************************************************************
* NAME
*
* glp_ios_node_level - determine subproblem level
*
* SYNOPSIS
*
* int glp_ios_node_level(glp_tree *tree, int p);
*
* RETURNS
*
* The routine glp_ios_node_level returns the level of the subproblem,
* whose reference number is p, in the branch-and-bound tree. (The root
* subproblem has level 0, and the level of any other subproblem is the
* level of its parent plus one.) */
int glp_ios_node_level(glp_tree *tree, int p)
{ IOSNPD *node;
/* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen"
"ce number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* return the node level */
return node->level;
}
/***********************************************************************
* NAME
*
* glp_ios_node_bound - determine subproblem local bound
*
* SYNOPSIS
*
* double glp_ios_node_bound(glp_tree *tree, int p);
*
* RETURNS
*
* The routine glp_ios_node_bound returns the local bound for (active or
* inactive) subproblem, whose reference number is p.
*
* COMMENTS
*
* The local bound for subproblem p is an lower (minimization) or upper
* (maximization) bound for integer optimal solution to this subproblem
* (not to the original problem). This bound is local in the sense that
* only subproblems in the subtree rooted at node p cannot have better
* integer feasible solutions.
*
* On creating a subproblem (due to the branching step) its local bound
* is inherited from its parent and then may get only stronger (never
* weaker). For the root subproblem its local bound is initially set to
* -DBL_MAX (minimization) or +DBL_MAX (maximization) and then improved
* as the root LP relaxation has been solved.
*
* Note that the local bound is not necessarily the optimal objective
* value to corresponding LP relaxation; it may be stronger. */
double glp_ios_node_bound(glp_tree *tree, int p)
{ IOSNPD *node;
/* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_node_bound: p = %d; invalid subproblem referen"
"ce number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* return the node local bound */
return node->bound;
}
/***********************************************************************
* NAME
*
* glp_ios_best_node - find active subproblem with best local bound
*
* SYNOPSIS
*
* int glp_ios_best_node(glp_tree *tree);
*
* RETURNS
*
* The routine glp_ios_best_node returns the reference number of the
* active subproblem, whose local bound is best (i.e. smallest in case
* of minimization or largest in case of maximization). However, if the
* tree is empty, the routine returns zero.
*
* COMMENTS
*
* The best local bound is an lower (minimization) or upper
* (maximization) bound for integer optimal solution to the original
* MIP problem. */
int glp_ios_best_node(glp_tree *tree)
{ return
ios_best_node(tree);
}
/***********************************************************************
* NAME
*
* glp_ios_mip_gap - compute relative MIP gap
*
* SYNOPSIS
*
* double glp_ios_mip_gap(glp_tree *tree);
*
* DESCRIPTION
*
* The routine glp_ios_mip_gap computes the relative MIP gap with the
* following formula:
*
* gap = |best_mip - best_bnd| / (|best_mip| + DBL_EPSILON),
*
* where best_mip is the best integer feasible solution found so far,
* best_bnd is the best (global) bound. If no integer feasible solution
* has been found yet, gap is set to DBL_MAX.
*
* RETURNS
*
* The routine glp_ios_mip_gap returns the relative MIP gap. */
double glp_ios_mip_gap(glp_tree *tree)
{ return
ios_relative_gap(tree);
}
/***********************************************************************
* NAME
*
* glp_ios_node_data - access subproblem application-specific data
*
* SYNOPSIS
*
* void *glp_ios_node_data(glp_tree *tree, int p);
*
* DESCRIPTION
*
* The routine glp_ios_node_data allows the application accessing a
* memory block allocated for the subproblem (which may be active or
* inactive), whose reference number is p.
*
* The size of the block is defined by the control parameter cb_size
* passed to the routine glp_intopt. The block is initialized by binary
* zeros on creating corresponding subproblem, and its contents is kept
* until the subproblem will be removed from the tree.
*
* The application may use these memory blocks to store specific data
* for each subproblem.
*
* RETURNS
*
* The routine glp_ios_node_data returns a pointer to the memory block
* for the specified subproblem. Note that if cb_size = 0, the routine
* returns a null pointer. */
void *glp_ios_node_data(glp_tree *tree, int p)
{ IOSNPD *node;
/* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen"
"ce number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* return pointer to the application-specific data */
return node->data;
}
/***********************************************************************
* NAME
*
* glp_ios_row_attr - retrieve additional row attributes
*
* SYNOPSIS
*
* void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr);
*
* DESCRIPTION
*
* The routine glp_ios_row_attr retrieves additional attributes of row
* i and stores them in the structure glp_attr. */
void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr)
{ GLPROW *row;
if (!(1 <= i && i <= tree->mip->m))
xerror("glp_ios_row_attr: i = %d; row number out of range\n",
i);
row = tree->mip->row[i];
attr->level = row->level;
attr->origin = row->origin;
attr->klass = row->klass;
return;
}
/**********************************************************************/
int glp_ios_pool_size(glp_tree *tree)
{ /* determine current size of the cut pool */
if (tree->reason != GLP_ICUTGEN)
xerror("glp_ios_pool_size: operation not allowed\n");
xassert(tree->local != NULL);
return tree->local->size;
}
/**********************************************************************/
int glp_ios_add_row(glp_tree *tree,
const char *name, int klass, int flags, int len, const int ind[],
const double val[], int type, double rhs)
{ /* add row (constraint) to the cut pool */
int num;
if (tree->reason != GLP_ICUTGEN)
xerror("glp_ios_add_row: operation not allowed\n");
xassert(tree->local != NULL);
num = ios_add_row(tree, tree->local, name, klass, flags, len,
ind, val, type, rhs);
return num;
}
/**********************************************************************/
void glp_ios_del_row(glp_tree *tree, int i)
{ /* remove row (constraint) from the cut pool */
if (tree->reason != GLP_ICUTGEN)
xerror("glp_ios_del_row: operation not allowed\n");
ios_del_row(tree, tree->local, i);
return;
}
/**********************************************************************/
void glp_ios_clear_pool(glp_tree *tree)
{ /* remove all rows (constraints) from the cut pool */
if (tree->reason != GLP_ICUTGEN)
xerror("glp_ios_clear_pool: operation not allowed\n");
ios_clear_pool(tree, tree->local);
return;
}
/***********************************************************************
* NAME
*
* glp_ios_can_branch - check if can branch upon specified variable
*
* SYNOPSIS
*
* int glp_ios_can_branch(glp_tree *tree, int j);
*
* RETURNS
*
* If j-th variable (column) can be used to branch upon, the routine
* glp_ios_can_branch returns non-zero, otherwise zero. */
int glp_ios_can_branch(glp_tree *tree, int j)
{ if (!(1 <= j && j <= tree->mip->n))
xerror("glp_ios_can_branch: j = %d; column number out of range"
"\n", j);
return tree->non_int[j];
}
/***********************************************************************
* NAME
*
* glp_ios_branch_upon - choose variable to branch upon
*
* SYNOPSIS
*
* void glp_ios_branch_upon(glp_tree *tree, int j, int sel);
*
* DESCRIPTION
*
* The routine glp_ios_branch_upon can be called from the user-defined
* callback routine in response to the reason GLP_IBRANCH to choose a
* branching variable, whose ordinal number is j. Should note that only
* variables, for which the routine glp_ios_can_branch returns non-zero,
* can be used to branch upon.
*
* The parameter sel is a flag that indicates which branch (subproblem)
* should be selected next to continue the search:
*
* GLP_DN_BRNCH - select down-branch;
* GLP_UP_BRNCH - select up-branch;
* GLP_NO_BRNCH - use general selection technique. */
void glp_ios_branch_upon(glp_tree *tree, int j, int sel)
{ if (!(1 <= j && j <= tree->mip->n))
xerror("glp_ios_branch_upon: j = %d; column number out of rang"
"e\n", j);
if (!(sel == GLP_DN_BRNCH || sel == GLP_UP_BRNCH ||
sel == GLP_NO_BRNCH))
xerror("glp_ios_branch_upon: sel = %d: invalid branch selectio"
"n flag\n", sel);
if (!(tree->non_int[j]))
xerror("glp_ios_branch_upon: j = %d; variable cannot be used t"
"o branch upon\n", j);
if (tree->br_var != 0)
xerror("glp_ios_branch_upon: branching variable already chosen"
"\n");
tree->br_var = j;
tree->br_sel = sel;
return;
}
/***********************************************************************
* NAME
*
* glp_ios_select_node - select subproblem to continue the search
*
* SYNOPSIS
*
* void glp_ios_select_node(glp_tree *tree, int p);
*
* DESCRIPTION
*
* The routine glp_ios_select_node can be called from the user-defined
* callback routine in response to the reason GLP_ISELECT to select an
* active subproblem, whose reference number is p. The search will be
* continued from the subproblem selected. */
void glp_ios_select_node(glp_tree *tree, int p)
{ IOSNPD *node;
/* obtain pointer to the specified subproblem */
if (!(1 <= p && p <= tree->nslots))
err: xerror("glp_ios_select_node: p = %d; invalid subproblem refere"
"nce number\n", p);
node = tree->slot[p].node;
if (node == NULL) goto err;
/* the specified subproblem must be active */
if (node->count != 0)
xerror("glp_ios_select_node: p = %d; subproblem not in the act"
"ive list\n", p);
/* no subproblem must be selected yet */
if (tree->next_p != 0)
xerror("glp_ios_select_node: subproblem already selected\n");
/* select the specified subproblem to continue the search */
tree->next_p = p;
return;
}
/***********************************************************************
* NAME
*
* glp_ios_heur_sol - provide solution found by heuristic
*
* SYNOPSIS
*
* int glp_ios_heur_sol(glp_tree *tree, const double x[]);
*
* DESCRIPTION
*
* The routine glp_ios_heur_sol can be called from the user-defined
* callback routine in response to the reason GLP_IHEUR to provide an
* integer feasible solution found by a primal heuristic.
*
* Primal values of *all* variables (columns) found by the heuristic
* should be placed in locations x[1], ..., x[n], where n is the number
* of columns in the original problem object. Note that the routine
* glp_ios_heur_sol *does not* check primal feasibility of the solution
* provided.
*
* Using the solution passed in the array x the routine computes value
* of the objective function. If the objective value is better than the
* best known integer feasible solution, the routine computes values of
* auxiliary variables (rows) and stores all solution components in the
* problem object.
*
* RETURNS
*
* If the provided solution is accepted, the routine glp_ios_heur_sol
* returns zero. Otherwise, if the provided solution is rejected, the
* routine returns non-zero. */
int glp_ios_heur_sol(glp_tree *tree, const double x[])
{ glp_prob *mip = tree->mip;
int m = tree->orig_m;
int n = tree->n;
int i, j;
double obj;
xassert(mip->m >= m);
xassert(mip->n == n);
/* check values of integer variables and compute value of the
objective function */
obj = mip->c0;
for (j = 1; j <= n; j++)
{ GLPCOL *col = mip->col[j];
if (col->kind == GLP_IV)
{ /* provided value must be integral */
if (x[j] != floor(x[j])) return 1;
}
obj += col->coef * x[j];
}
/* check if the provided solution is better than the best known
integer feasible solution */
if (mip->mip_stat == GLP_FEAS)
{ switch (mip->dir)
{ case GLP_MIN:
if (obj >= tree->mip->mip_obj) return 1;
break;
case GLP_MAX:
if (obj <= tree->mip->mip_obj) return 1;
break;
default:
xassert(mip != mip);
}
}
/* it is better; store it in the problem object */
if (tree->parm->msg_lev >= GLP_MSG_ON)
xprintf("Solution found by heuristic: %.12g\n", obj);
mip->mip_stat = GLP_FEAS;
mip->mip_obj = obj;
for (j = 1; j <= n; j++)
mip->col[j]->mipx = x[j];
for (i = 1; i <= m; i++)
{ GLPROW *row = mip->row[i];
GLPAIJ *aij;
row->mipx = 0.0;
for (aij = row->ptr; aij != NULL; aij = aij->r_next)
row->mipx += aij->val * aij->col->mipx;
}
#if 1 /* 11/VII-2013 */
ios_process_sol(tree);
#endif
return 0;
}
/***********************************************************************
* NAME
*
* glp_ios_terminate - terminate the solution process.
*
* SYNOPSIS
*
* void glp_ios_terminate(glp_tree *tree);
*
* DESCRIPTION
*
* The routine glp_ios_terminate sets a flag indicating that the MIP
* solver should prematurely terminate the search. */
void glp_ios_terminate(glp_tree *tree)
{ if (tree->parm->msg_lev >= GLP_MSG_DBG)
xprintf("The search is prematurely terminated due to applicati"
"on request\n");
tree->stop = 1;
return;
}
/* eof */