From feb8ebaeb76fa1c94de2dd7c4e5a0999b313f8c6 Mon Sep 17 00:00:00 2001 From: David Monniaux Date: Thu, 6 Jun 2019 20:09:32 +0200 Subject: GLPK 4.65 --- test/monniaux/glpk-4.65/src/npp/npp2.c | 1433 ++++++++++++++++++++++++++++++++ 1 file changed, 1433 insertions(+) create mode 100644 test/monniaux/glpk-4.65/src/npp/npp2.c (limited to 'test/monniaux/glpk-4.65/src/npp/npp2.c') diff --git a/test/monniaux/glpk-4.65/src/npp/npp2.c b/test/monniaux/glpk-4.65/src/npp/npp2.c new file mode 100644 index 00000000..4efcf1d1 --- /dev/null +++ b/test/monniaux/glpk-4.65/src/npp/npp2.c @@ -0,0 +1,1433 @@ +/* npp2.c */ + +/*********************************************************************** +* This code is part of GLPK (GNU Linear Programming Kit). +* +* Copyright (C) 2009-2017 Andrew Makhorin, Department for Applied +* Informatics, Moscow Aviation Institute, Moscow, Russia. All rights +* reserved. E-mail: . +* +* 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 . +***********************************************************************/ + +#include "env.h" +#include "npp.h" + +/*********************************************************************** +* NAME +* +* npp_free_row - process free (unbounded) row +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_free_row(NPP *npp, NPPROW *p); +* +* DESCRIPTION +* +* The routine npp_free_row processes row p, which is free (i.e. has +* no finite bounds): +* +* -inf < sum a[p,j] x[j] < +inf. (1) +* j +* +* PROBLEM TRANSFORMATION +* +* Constraint (1) cannot be active, so it is redundant and can be +* removed from the original problem. +* +* Removing row p leads to removing a column of multiplier pi[p] for +* this row in the dual system. Since row p has no bounds, pi[p] = 0, +* so removing the column does not affect the dual solution. +* +* RECOVERING BASIC SOLUTION +* +* In solution to the original problem row p is inactive constraint, +* so it is assigned status GLP_BS, and multiplier pi[p] is assigned +* zero value. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* In solution to the original problem row p is inactive constraint, +* so its multiplier pi[p] is assigned zero value. +* +* RECOVERING MIP SOLUTION +* +* None needed. */ + +struct free_row +{ /* free (unbounded) row */ + int p; + /* row reference number */ +}; + +static int rcv_free_row(NPP *npp, void *info); + +void npp_free_row(NPP *npp, NPPROW *p) +{ /* process free (unbounded) row */ + struct free_row *info; + /* the row must be free */ + xassert(p->lb == -DBL_MAX && p->ub == +DBL_MAX); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_free_row, sizeof(struct free_row)); + info->p = p->i; + /* remove the row from the problem */ + npp_del_row(npp, p); + return; +} + +static int rcv_free_row(NPP *npp, void *_info) +{ /* recover free (unbounded) row */ + struct free_row *info = _info; + if (npp->sol == GLP_SOL) + npp->r_stat[info->p] = GLP_BS; + if (npp->sol != GLP_MIP) + npp->r_pi[info->p] = 0.0; + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_geq_row - process row of 'not less than' type +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_geq_row(NPP *npp, NPPROW *p); +* +* DESCRIPTION +* +* The routine npp_geq_row processes row p, which is 'not less than' +* inequality constraint: +* +* L[p] <= sum a[p,j] x[j] (<= U[p]), (1) +* j +* +* where L[p] < U[p], and upper bound may not exist (U[p] = +oo). +* +* PROBLEM TRANSFORMATION +* +* Constraint (1) can be replaced by equality constraint: +* +* sum a[p,j] x[j] - s = L[p], (2) +* j +* +* where +* +* 0 <= s (<= U[p] - L[p]) (3) +* +* is a non-negative surplus variable. +* +* Since in the primal system there appears column s having the only +* non-zero coefficient in row p, in the dual system there appears a +* new row: +* +* (-1) pi[p] + lambda = 0, (4) +* +* where (-1) is coefficient of column s in row p, pi[p] is multiplier +* of row p, lambda is multiplier of column q, 0 is coefficient of +* column s in the objective row. +* +* RECOVERING BASIC SOLUTION +* +* Status of row p in solution to the original problem is determined +* by its status and status of column q in solution to the transformed +* problem as follows: +* +* +--------------------------------------+------------------+ +* | Transformed problem | Original problem | +* +-----------------+--------------------+------------------+ +* | Status of row p | Status of column s | Status of row p | +* +-----------------+--------------------+------------------+ +* | GLP_BS | GLP_BS | N/A | +* | GLP_BS | GLP_NL | GLP_BS | +* | GLP_BS | GLP_NU | GLP_BS | +* | GLP_NS | GLP_BS | GLP_BS | +* | GLP_NS | GLP_NL | GLP_NL | +* | GLP_NS | GLP_NU | GLP_NU | +* +-----------------+--------------------+------------------+ +* +* Value of row multiplier pi[p] in solution to the original problem +* is the same as in solution to the transformed problem. +* +* 1. In solution to the transformed problem row p and column q cannot +* be basic at the same time; otherwise the basis matrix would have +* two linear dependent columns: unity column of auxiliary variable +* of row p and unity column of variable s. +* +* 2. Though in the transformed problem row p is equality constraint, +* it may be basic due to primal degenerate solution. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of row multiplier pi[p] in solution to the original problem +* is the same as in solution to the transformed problem. +* +* RECOVERING MIP SOLUTION +* +* None needed. */ + +struct ineq_row +{ /* inequality constraint row */ + int p; + /* row reference number */ + int s; + /* column reference number for slack/surplus variable */ +}; + +static int rcv_geq_row(NPP *npp, void *info); + +void npp_geq_row(NPP *npp, NPPROW *p) +{ /* process row of 'not less than' type */ + struct ineq_row *info; + NPPCOL *s; + /* the row must have lower bound */ + xassert(p->lb != -DBL_MAX); + xassert(p->lb < p->ub); + /* create column for surplus variable */ + s = npp_add_col(npp); + s->lb = 0.0; + s->ub = (p->ub == +DBL_MAX ? +DBL_MAX : p->ub - p->lb); + /* and add it to the transformed problem */ + npp_add_aij(npp, p, s, -1.0); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_geq_row, sizeof(struct ineq_row)); + info->p = p->i; + info->s = s->j; + /* replace the row by equality constraint */ + p->ub = p->lb; + return; +} + +static int rcv_geq_row(NPP *npp, void *_info) +{ /* recover row of 'not less than' type */ + struct ineq_row *info = _info; + if (npp->sol == GLP_SOL) + { if (npp->r_stat[info->p] == GLP_BS) + { if (npp->c_stat[info->s] == GLP_BS) + { npp_error(); + return 1; + } + else if (npp->c_stat[info->s] == GLP_NL || + npp->c_stat[info->s] == GLP_NU) + npp->r_stat[info->p] = GLP_BS; + else + { npp_error(); + return 1; + } + } + else if (npp->r_stat[info->p] == GLP_NS) + { if (npp->c_stat[info->s] == GLP_BS) + npp->r_stat[info->p] = GLP_BS; + else if (npp->c_stat[info->s] == GLP_NL) + npp->r_stat[info->p] = GLP_NL; + else if (npp->c_stat[info->s] == GLP_NU) + npp->r_stat[info->p] = GLP_NU; + else + { npp_error(); + return 1; + } + } + else + { npp_error(); + return 1; + } + } + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_leq_row - process row of 'not greater than' type +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_leq_row(NPP *npp, NPPROW *p); +* +* DESCRIPTION +* +* The routine npp_leq_row processes row p, which is 'not greater than' +* inequality constraint: +* +* (L[p] <=) sum a[p,j] x[j] <= U[p], (1) +* j +* +* where L[p] < U[p], and lower bound may not exist (L[p] = +oo). +* +* PROBLEM TRANSFORMATION +* +* Constraint (1) can be replaced by equality constraint: +* +* sum a[p,j] x[j] + s = L[p], (2) +* j +* +* where +* +* 0 <= s (<= U[p] - L[p]) (3) +* +* is a non-negative slack variable. +* +* Since in the primal system there appears column s having the only +* non-zero coefficient in row p, in the dual system there appears a +* new row: +* +* (+1) pi[p] + lambda = 0, (4) +* +* where (+1) is coefficient of column s in row p, pi[p] is multiplier +* of row p, lambda is multiplier of column q, 0 is coefficient of +* column s in the objective row. +* +* RECOVERING BASIC SOLUTION +* +* Status of row p in solution to the original problem is determined +* by its status and status of column q in solution to the transformed +* problem as follows: +* +* +--------------------------------------+------------------+ +* | Transformed problem | Original problem | +* +-----------------+--------------------+------------------+ +* | Status of row p | Status of column s | Status of row p | +* +-----------------+--------------------+------------------+ +* | GLP_BS | GLP_BS | N/A | +* | GLP_BS | GLP_NL | GLP_BS | +* | GLP_BS | GLP_NU | GLP_BS | +* | GLP_NS | GLP_BS | GLP_BS | +* | GLP_NS | GLP_NL | GLP_NU | +* | GLP_NS | GLP_NU | GLP_NL | +* +-----------------+--------------------+------------------+ +* +* Value of row multiplier pi[p] in solution to the original problem +* is the same as in solution to the transformed problem. +* +* 1. In solution to the transformed problem row p and column q cannot +* be basic at the same time; otherwise the basis matrix would have +* two linear dependent columns: unity column of auxiliary variable +* of row p and unity column of variable s. +* +* 2. Though in the transformed problem row p is equality constraint, +* it may be basic due to primal degeneracy. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of row multiplier pi[p] in solution to the original problem +* is the same as in solution to the transformed problem. +* +* RECOVERING MIP SOLUTION +* +* None needed. */ + +static int rcv_leq_row(NPP *npp, void *info); + +void npp_leq_row(NPP *npp, NPPROW *p) +{ /* process row of 'not greater than' type */ + struct ineq_row *info; + NPPCOL *s; + /* the row must have upper bound */ + xassert(p->ub != +DBL_MAX); + xassert(p->lb < p->ub); + /* create column for slack variable */ + s = npp_add_col(npp); + s->lb = 0.0; + s->ub = (p->lb == -DBL_MAX ? +DBL_MAX : p->ub - p->lb); + /* and add it to the transformed problem */ + npp_add_aij(npp, p, s, +1.0); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_leq_row, sizeof(struct ineq_row)); + info->p = p->i; + info->s = s->j; + /* replace the row by equality constraint */ + p->lb = p->ub; + return; +} + +static int rcv_leq_row(NPP *npp, void *_info) +{ /* recover row of 'not greater than' type */ + struct ineq_row *info = _info; + if (npp->sol == GLP_SOL) + { if (npp->r_stat[info->p] == GLP_BS) + { if (npp->c_stat[info->s] == GLP_BS) + { npp_error(); + return 1; + } + else if (npp->c_stat[info->s] == GLP_NL || + npp->c_stat[info->s] == GLP_NU) + npp->r_stat[info->p] = GLP_BS; + else + { npp_error(); + return 1; + } + } + else if (npp->r_stat[info->p] == GLP_NS) + { if (npp->c_stat[info->s] == GLP_BS) + npp->r_stat[info->p] = GLP_BS; + else if (npp->c_stat[info->s] == GLP_NL) + npp->r_stat[info->p] = GLP_NU; + else if (npp->c_stat[info->s] == GLP_NU) + npp->r_stat[info->p] = GLP_NL; + else + { npp_error(); + return 1; + } + } + else + { npp_error(); + return 1; + } + } + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_free_col - process free (unbounded) column +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_free_col(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_free_col processes column q, which is free (i.e. has +* no finite bounds): +* +* -oo < x[q] < +oo. (1) +* +* PROBLEM TRANSFORMATION +* +* Free (unbounded) variable can be replaced by the difference of two +* non-negative variables: +* +* x[q] = s' - s'', s', s'' >= 0. (2) +* +* Assuming that in the transformed problem x[q] becomes s', +* transformation (2) causes new column s'' to appear, which differs +* from column s' only in the sign of coefficients in constraint and +* objective rows. Thus, if in the dual system the following row +* corresponds to column s': +* +* sum a[i,q] pi[i] + lambda' = c[q], (3) +* i +* +* the row which corresponds to column s'' is the following: +* +* sum (-a[i,q]) pi[i] + lambda'' = -c[q]. (4) +* i +* +* Then from (3) and (4) it follows that: +* +* lambda' + lambda'' = 0 => lambda' = lmabda'' = 0, (5) +* +* where lambda' and lambda'' are multipliers for columns s' and s'', +* resp. +* +* RECOVERING BASIC SOLUTION +* +* With respect to (5) status of column q in solution to the original +* problem is determined by statuses of columns s' and s'' in solution +* to the transformed problem as follows: +* +* +--------------------------------------+------------------+ +* | Transformed problem | Original problem | +* +------------------+-------------------+------------------+ +* | Status of col s' | Status of col s'' | Status of col q | +* +------------------+-------------------+------------------+ +* | GLP_BS | GLP_BS | N/A | +* | GLP_BS | GLP_NL | GLP_BS | +* | GLP_NL | GLP_BS | GLP_BS | +* | GLP_NL | GLP_NL | GLP_NF | +* +------------------+-------------------+------------------+ +* +* Value of column q is computed with formula (2). +* +* 1. In solution to the transformed problem columns s' and s'' cannot +* be basic at the same time, because they differ only in the sign, +* hence, are linear dependent. +* +* 2. Though column q is free, it can be non-basic due to dual +* degeneracy. +* +* 3. If column q is integral, columns s' and s'' are also integral. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of column q is computed with formula (2). +* +* RECOVERING MIP SOLUTION +* +* Value of column q is computed with formula (2). */ + +struct free_col +{ /* free (unbounded) column */ + int q; + /* column reference number for variables x[q] and s' */ + int s; + /* column reference number for variable s'' */ +}; + +static int rcv_free_col(NPP *npp, void *info); + +void npp_free_col(NPP *npp, NPPCOL *q) +{ /* process free (unbounded) column */ + struct free_col *info; + NPPCOL *s; + NPPAIJ *aij; + /* the column must be free */ + xassert(q->lb == -DBL_MAX && q->ub == +DBL_MAX); + /* variable x[q] becomes s' */ + q->lb = 0.0, q->ub = +DBL_MAX; + /* create variable s'' */ + s = npp_add_col(npp); + s->is_int = q->is_int; + s->lb = 0.0, s->ub = +DBL_MAX; + /* duplicate objective coefficient */ + s->coef = -q->coef; + /* duplicate column of the constraint matrix */ + for (aij = q->ptr; aij != NULL; aij = aij->c_next) + npp_add_aij(npp, aij->row, s, -aij->val); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_free_col, sizeof(struct free_col)); + info->q = q->j; + info->s = s->j; + return; +} + +static int rcv_free_col(NPP *npp, void *_info) +{ /* recover free (unbounded) column */ + struct free_col *info = _info; + if (npp->sol == GLP_SOL) + { if (npp->c_stat[info->q] == GLP_BS) + { if (npp->c_stat[info->s] == GLP_BS) + { npp_error(); + return 1; + } + else if (npp->c_stat[info->s] == GLP_NL) + npp->c_stat[info->q] = GLP_BS; + else + { npp_error(); + return -1; + } + } + else if (npp->c_stat[info->q] == GLP_NL) + { if (npp->c_stat[info->s] == GLP_BS) + npp->c_stat[info->q] = GLP_BS; + else if (npp->c_stat[info->s] == GLP_NL) + npp->c_stat[info->q] = GLP_NF; + else + { npp_error(); + return -1; + } + } + else + { npp_error(); + return -1; + } + } + /* compute value of x[q] with formula (2) */ + npp->c_value[info->q] -= npp->c_value[info->s]; + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_lbnd_col - process column with (non-zero) lower bound +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_lbnd_col(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_lbnd_col processes column q, which has (non-zero) +* lower bound: +* +* l[q] <= x[q] (<= u[q]), (1) +* +* where l[q] < u[q], and upper bound may not exist (u[q] = +oo). +* +* PROBLEM TRANSFORMATION +* +* Column q can be replaced as follows: +* +* x[q] = l[q] + s, (2) +* +* where +* +* 0 <= s (<= u[q] - l[q]) (3) +* +* is a non-negative variable. +* +* Substituting x[q] from (2) into the objective row, we have: +* +* z = sum c[j] x[j] + c0 = +* j +* +* = sum c[j] x[j] + c[q] x[q] + c0 = +* j!=q +* +* = sum c[j] x[j] + c[q] (l[q] + s) + c0 = +* j!=q +* +* = sum c[j] x[j] + c[q] s + c~0, +* +* where +* +* c~0 = c0 + c[q] l[q] (4) +* +* is the constant term of the objective in the transformed problem. +* Similarly, substituting x[q] into constraint row i, we have: +* +* L[i] <= sum a[i,j] x[j] <= U[i] ==> +* j +* +* L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> +* j!=q +* +* L[i] <= sum a[i,j] x[j] + a[i,q] (l[q] + s) <= U[i] ==> +* j!=q +* +* L~[i] <= sum a[i,j] x[j] + a[i,q] s <= U~[i], +* j!=q +* +* where +* +* L~[i] = L[i] - a[i,q] l[q], U~[i] = U[i] - a[i,q] l[q] (5) +* +* are lower and upper bounds of row i in the transformed problem, +* resp. +* +* Transformation (2) does not affect the dual system. +* +* RECOVERING BASIC SOLUTION +* +* Status of column q in solution to the original problem is the same +* as in solution to the transformed problem (GLP_BS, GLP_NL or GLP_NU). +* Value of column q is computed with formula (2). +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of column q is computed with formula (2). +* +* RECOVERING MIP SOLUTION +* +* Value of column q is computed with formula (2). */ + +struct bnd_col +{ /* bounded column */ + int q; + /* column reference number for variables x[q] and s */ + double bnd; + /* lower/upper bound l[q] or u[q] */ +}; + +static int rcv_lbnd_col(NPP *npp, void *info); + +void npp_lbnd_col(NPP *npp, NPPCOL *q) +{ /* process column with (non-zero) lower bound */ + struct bnd_col *info; + NPPROW *i; + NPPAIJ *aij; + /* the column must have non-zero lower bound */ + xassert(q->lb != 0.0); + xassert(q->lb != -DBL_MAX); + xassert(q->lb < q->ub); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_lbnd_col, sizeof(struct bnd_col)); + info->q = q->j; + info->bnd = q->lb; + /* substitute x[q] into objective row */ + npp->c0 += q->coef * q->lb; + /* substitute x[q] into constraint rows */ + for (aij = q->ptr; aij != NULL; aij = aij->c_next) + { i = aij->row; + if (i->lb == i->ub) + i->ub = (i->lb -= aij->val * q->lb); + else + { if (i->lb != -DBL_MAX) + i->lb -= aij->val * q->lb; + if (i->ub != +DBL_MAX) + i->ub -= aij->val * q->lb; + } + } + /* column x[q] becomes column s */ + if (q->ub != +DBL_MAX) + q->ub -= q->lb; + q->lb = 0.0; + return; +} + +static int rcv_lbnd_col(NPP *npp, void *_info) +{ /* recover column with (non-zero) lower bound */ + struct bnd_col *info = _info; + if (npp->sol == GLP_SOL) + { if (npp->c_stat[info->q] == GLP_BS || + npp->c_stat[info->q] == GLP_NL || + npp->c_stat[info->q] == GLP_NU) + npp->c_stat[info->q] = npp->c_stat[info->q]; + else + { npp_error(); + return 1; + } + } + /* compute value of x[q] with formula (2) */ + npp->c_value[info->q] = info->bnd + npp->c_value[info->q]; + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_ubnd_col - process column with upper bound +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_ubnd_col(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_ubnd_col processes column q, which has upper bound: +* +* (l[q] <=) x[q] <= u[q], (1) +* +* where l[q] < u[q], and lower bound may not exist (l[q] = -oo). +* +* PROBLEM TRANSFORMATION +* +* Column q can be replaced as follows: +* +* x[q] = u[q] - s, (2) +* +* where +* +* 0 <= s (<= u[q] - l[q]) (3) +* +* is a non-negative variable. +* +* Substituting x[q] from (2) into the objective row, we have: +* +* z = sum c[j] x[j] + c0 = +* j +* +* = sum c[j] x[j] + c[q] x[q] + c0 = +* j!=q +* +* = sum c[j] x[j] + c[q] (u[q] - s) + c0 = +* j!=q +* +* = sum c[j] x[j] - c[q] s + c~0, +* +* where +* +* c~0 = c0 + c[q] u[q] (4) +* +* is the constant term of the objective in the transformed problem. +* Similarly, substituting x[q] into constraint row i, we have: +* +* L[i] <= sum a[i,j] x[j] <= U[i] ==> +* j +* +* L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> +* j!=q +* +* L[i] <= sum a[i,j] x[j] + a[i,q] (u[q] - s) <= U[i] ==> +* j!=q +* +* L~[i] <= sum a[i,j] x[j] - a[i,q] s <= U~[i], +* j!=q +* +* where +* +* L~[i] = L[i] - a[i,q] u[q], U~[i] = U[i] - a[i,q] u[q] (5) +* +* are lower and upper bounds of row i in the transformed problem, +* resp. +* +* Note that in the transformed problem coefficients c[q] and a[i,q] +* change their sign. Thus, the row of the dual system corresponding to +* column q: +* +* sum a[i,q] pi[i] + lambda[q] = c[q] (6) +* i +* +* in the transformed problem becomes the following: +* +* sum (-a[i,q]) pi[i] + lambda[s] = -c[q]. (7) +* i +* +* Therefore: +* +* lambda[q] = - lambda[s], (8) +* +* where lambda[q] is multiplier for column q, lambda[s] is multiplier +* for column s. +* +* RECOVERING BASIC SOLUTION +* +* With respect to (8) status of column q in solution to the original +* problem is determined by status of column s in solution to the +* transformed problem as follows: +* +* +-----------------------+--------------------+ +* | Status of column s | Status of column q | +* | (transformed problem) | (original problem) | +* +-----------------------+--------------------+ +* | GLP_BS | GLP_BS | +* | GLP_NL | GLP_NU | +* | GLP_NU | GLP_NL | +* +-----------------------+--------------------+ +* +* Value of column q is computed with formula (2). +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of column q is computed with formula (2). +* +* RECOVERING MIP SOLUTION +* +* Value of column q is computed with formula (2). */ + +static int rcv_ubnd_col(NPP *npp, void *info); + +void npp_ubnd_col(NPP *npp, NPPCOL *q) +{ /* process column with upper bound */ + struct bnd_col *info; + NPPROW *i; + NPPAIJ *aij; + /* the column must have upper bound */ + xassert(q->ub != +DBL_MAX); + xassert(q->lb < q->ub); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_ubnd_col, sizeof(struct bnd_col)); + info->q = q->j; + info->bnd = q->ub; + /* substitute x[q] into objective row */ + npp->c0 += q->coef * q->ub; + q->coef = -q->coef; + /* substitute x[q] into constraint rows */ + for (aij = q->ptr; aij != NULL; aij = aij->c_next) + { i = aij->row; + if (i->lb == i->ub) + i->ub = (i->lb -= aij->val * q->ub); + else + { if (i->lb != -DBL_MAX) + i->lb -= aij->val * q->ub; + if (i->ub != +DBL_MAX) + i->ub -= aij->val * q->ub; + } + aij->val = -aij->val; + } + /* column x[q] becomes column s */ + if (q->lb != -DBL_MAX) + q->ub -= q->lb; + else + q->ub = +DBL_MAX; + q->lb = 0.0; + return; +} + +static int rcv_ubnd_col(NPP *npp, void *_info) +{ /* recover column with upper bound */ + struct bnd_col *info = _info; + if (npp->sol == GLP_BS) + { if (npp->c_stat[info->q] == GLP_BS) + npp->c_stat[info->q] = GLP_BS; + else if (npp->c_stat[info->q] == GLP_NL) + npp->c_stat[info->q] = GLP_NU; + else if (npp->c_stat[info->q] == GLP_NU) + npp->c_stat[info->q] = GLP_NL; + else + { npp_error(); + return 1; + } + } + /* compute value of x[q] with formula (2) */ + npp->c_value[info->q] = info->bnd - npp->c_value[info->q]; + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_dbnd_col - process non-negative column with upper bound +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_dbnd_col(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_dbnd_col processes column q, which is non-negative +* and has upper bound: +* +* 0 <= x[q] <= u[q], (1) +* +* where u[q] > 0. +* +* PROBLEM TRANSFORMATION +* +* Upper bound of column q can be replaced by the following equality +* constraint: +* +* x[q] + s = u[q], (2) +* +* where s >= 0 is a non-negative complement variable. +* +* Since in the primal system along with new row (2) there appears a +* new column s having the only non-zero coefficient in this row, in +* the dual system there appears a new row: +* +* (+1)pi + lambda[s] = 0, (3) +* +* where (+1) is coefficient at column s in row (2), pi is multiplier +* for row (2), lambda[s] is multiplier for column s, 0 is coefficient +* at column s in the objective row. +* +* RECOVERING BASIC SOLUTION +* +* Status of column q in solution to the original problem is determined +* by its status and status of column s in solution to the transformed +* problem as follows: +* +* +-----------------------------------+------------------+ +* | Transformed problem | Original problem | +* +-----------------+-----------------+------------------+ +* | Status of col q | Status of col s | Status of col q | +* +-----------------+-----------------+------------------+ +* | GLP_BS | GLP_BS | GLP_BS | +* | GLP_BS | GLP_NL | GLP_NU | +* | GLP_NL | GLP_BS | GLP_NL | +* | GLP_NL | GLP_NL | GLP_NL (*) | +* +-----------------+-----------------+------------------+ +* +* Value of column q in solution to the original problem is the same as +* in solution to the transformed problem. +* +* 1. Formally, in solution to the transformed problem columns q and s +* cannot be non-basic at the same time, since the constraint (2) +* would be violated. However, if u[q] is close to zero, violation +* may be less than a working precision even if both columns q and s +* are non-basic. In this degenerate case row (2) can be only basic, +* i.e. non-active constraint (otherwise corresponding row of the +* basis matrix would be zero). This allows to pivot out auxiliary +* variable and pivot in column s, in which case the row becomes +* active while column s becomes basic. +* +* 2. If column q is integral, column s is also integral. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of column q in solution to the original problem is the same as +* in solution to the transformed problem. +* +* RECOVERING MIP SOLUTION +* +* Value of column q in solution to the original problem is the same as +* in solution to the transformed problem. */ + +struct dbnd_col +{ /* double-bounded column */ + int q; + /* column reference number for variable x[q] */ + int s; + /* column reference number for complement variable s */ +}; + +static int rcv_dbnd_col(NPP *npp, void *info); + +void npp_dbnd_col(NPP *npp, NPPCOL *q) +{ /* process non-negative column with upper bound */ + struct dbnd_col *info; + NPPROW *p; + NPPCOL *s; + /* the column must be non-negative with upper bound */ + xassert(q->lb == 0.0); + xassert(q->ub > 0.0); + xassert(q->ub != +DBL_MAX); + /* create variable s */ + s = npp_add_col(npp); + s->is_int = q->is_int; + s->lb = 0.0, s->ub = +DBL_MAX; + /* create equality constraint (2) */ + p = npp_add_row(npp); + p->lb = p->ub = q->ub; + npp_add_aij(npp, p, q, +1.0); + npp_add_aij(npp, p, s, +1.0); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_dbnd_col, sizeof(struct dbnd_col)); + info->q = q->j; + info->s = s->j; + /* remove upper bound of x[q] */ + q->ub = +DBL_MAX; + return; +} + +static int rcv_dbnd_col(NPP *npp, void *_info) +{ /* recover non-negative column with upper bound */ + struct dbnd_col *info = _info; + if (npp->sol == GLP_BS) + { if (npp->c_stat[info->q] == GLP_BS) + { if (npp->c_stat[info->s] == GLP_BS) + npp->c_stat[info->q] = GLP_BS; + else if (npp->c_stat[info->s] == GLP_NL) + npp->c_stat[info->q] = GLP_NU; + else + { npp_error(); + return 1; + } + } + else if (npp->c_stat[info->q] == GLP_NL) + { if (npp->c_stat[info->s] == GLP_BS || + npp->c_stat[info->s] == GLP_NL) + npp->c_stat[info->q] = GLP_NL; + else + { npp_error(); + return 1; + } + } + else + { npp_error(); + return 1; + } + } + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_fixed_col - process fixed column +* +* SYNOPSIS +* +* #include "glpnpp.h" +* void npp_fixed_col(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_fixed_col processes column q, which is fixed: +* +* x[q] = s[q], (1) +* +* where s[q] is a fixed column value. +* +* PROBLEM TRANSFORMATION +* +* The value of a fixed column can be substituted into the objective +* and constraint rows that allows removing the column from the problem. +* +* Substituting x[q] = s[q] into the objective row, we have: +* +* z = sum c[j] x[j] + c0 = +* j +* +* = sum c[j] x[j] + c[q] x[q] + c0 = +* j!=q +* +* = sum c[j] x[j] + c[q] s[q] + c0 = +* j!=q +* +* = sum c[j] x[j] + c~0, +* j!=q +* +* where +* +* c~0 = c0 + c[q] s[q] (2) +* +* is the constant term of the objective in the transformed problem. +* Similarly, substituting x[q] = s[q] into constraint row i, we have: +* +* L[i] <= sum a[i,j] x[j] <= U[i] ==> +* j +* +* L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> +* j!=q +* +* L[i] <= sum a[i,j] x[j] + a[i,q] s[q] <= U[i] ==> +* j!=q +* +* L~[i] <= sum a[i,j] x[j] + a[i,q] s <= U~[i], +* j!=q +* +* where +* +* L~[i] = L[i] - a[i,q] s[q], U~[i] = U[i] - a[i,q] s[q] (3) +* +* are lower and upper bounds of row i in the transformed problem, +* resp. +* +* RECOVERING BASIC SOLUTION +* +* Column q is assigned status GLP_NS and its value is assigned s[q]. +* +* RECOVERING INTERIOR-POINT SOLUTION +* +* Value of column q is assigned s[q]. +* +* RECOVERING MIP SOLUTION +* +* Value of column q is assigned s[q]. */ + +struct fixed_col +{ /* fixed column */ + int q; + /* column reference number for variable x[q] */ + double s; + /* value, at which x[q] is fixed */ +}; + +static int rcv_fixed_col(NPP *npp, void *info); + +void npp_fixed_col(NPP *npp, NPPCOL *q) +{ /* process fixed column */ + struct fixed_col *info; + NPPROW *i; + NPPAIJ *aij; + /* the column must be fixed */ + xassert(q->lb == q->ub); + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_fixed_col, sizeof(struct fixed_col)); + info->q = q->j; + info->s = q->lb; + /* substitute x[q] = s[q] into objective row */ + npp->c0 += q->coef * q->lb; + /* substitute x[q] = s[q] into constraint rows */ + for (aij = q->ptr; aij != NULL; aij = aij->c_next) + { i = aij->row; + if (i->lb == i->ub) + i->ub = (i->lb -= aij->val * q->lb); + else + { if (i->lb != -DBL_MAX) + i->lb -= aij->val * q->lb; + if (i->ub != +DBL_MAX) + i->ub -= aij->val * q->lb; + } + } + /* remove the column from the problem */ + npp_del_col(npp, q); + return; +} + +static int rcv_fixed_col(NPP *npp, void *_info) +{ /* recover fixed column */ + struct fixed_col *info = _info; + if (npp->sol == GLP_SOL) + npp->c_stat[info->q] = GLP_NS; + npp->c_value[info->q] = info->s; + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_make_equality - process row with almost identical bounds +* +* SYNOPSIS +* +* #include "glpnpp.h" +* int npp_make_equality(NPP *npp, NPPROW *p); +* +* DESCRIPTION +* +* The routine npp_make_equality processes row p: +* +* L[p] <= sum a[p,j] x[j] <= U[p], (1) +* j +* +* where -oo < L[p] < U[p] < +oo, i.e. which is double-sided inequality +* constraint. +* +* RETURNS +* +* 0 - row bounds have not been changed; +* +* 1 - row has been replaced by equality constraint. +* +* PROBLEM TRANSFORMATION +* +* If bounds of row (1) are very close to each other: +* +* U[p] - L[p] <= eps, (2) +* +* where eps is an absolute tolerance for row value, the row can be +* replaced by the following almost equivalent equiality constraint: +* +* sum a[p,j] x[j] = b, (3) +* j +* +* where b = (L[p] + U[p]) / 2. If the right-hand side in (3) happens +* to be very close to its nearest integer: +* +* |b - floor(b + 0.5)| <= eps, (4) +* +* it is reasonable to use this nearest integer as the right-hand side. +* +* RECOVERING BASIC SOLUTION +* +* Status of row p in solution to the original problem is determined +* by its status and the sign of its multiplier pi[p] in solution to +* the transformed problem as follows: +* +* +-----------------------+---------+--------------------+ +* | Status of row p | Sign of | Status of row p | +* | (transformed problem) | pi[p] | (original problem) | +* +-----------------------+---------+--------------------+ +* | GLP_BS | + / - | GLP_BS | +* | GLP_NS | + | GLP_NL | +* | GLP_NS | - | GLP_NU | +* +-----------------------+---------+--------------------+ +* +* Value of row multiplier pi[p] in solution to the original problem is +* the same as in solution to the transformed problem. +* +* RECOVERING INTERIOR POINT SOLUTION +* +* Value of row multiplier pi[p] in solution to the original problem is +* the same as in solution to the transformed problem. +* +* RECOVERING MIP SOLUTION +* +* None needed. */ + +struct make_equality +{ /* row with almost identical bounds */ + int p; + /* row reference number */ +}; + +static int rcv_make_equality(NPP *npp, void *info); + +int npp_make_equality(NPP *npp, NPPROW *p) +{ /* process row with almost identical bounds */ + struct make_equality *info; + double b, eps, nint; + /* the row must be double-sided inequality */ + xassert(p->lb != -DBL_MAX); + xassert(p->ub != +DBL_MAX); + xassert(p->lb < p->ub); + /* check row bounds */ + eps = 1e-9 + 1e-12 * fabs(p->lb); + if (p->ub - p->lb > eps) return 0; + /* row bounds are very close to each other */ + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_make_equality, sizeof(struct make_equality)); + info->p = p->i; + /* compute right-hand side */ + b = 0.5 * (p->ub + p->lb); + nint = floor(b + 0.5); + if (fabs(b - nint) <= eps) b = nint; + /* replace row p by almost equivalent equality constraint */ + p->lb = p->ub = b; + return 1; +} + +int rcv_make_equality(NPP *npp, void *_info) +{ /* recover row with almost identical bounds */ + struct make_equality *info = _info; + if (npp->sol == GLP_SOL) + { if (npp->r_stat[info->p] == GLP_BS) + npp->r_stat[info->p] = GLP_BS; + else if (npp->r_stat[info->p] == GLP_NS) + { if (npp->r_pi[info->p] >= 0.0) + npp->r_stat[info->p] = GLP_NL; + else + npp->r_stat[info->p] = GLP_NU; + } + else + { npp_error(); + return 1; + } + } + return 0; +} + +/*********************************************************************** +* NAME +* +* npp_make_fixed - process column with almost identical bounds +* +* SYNOPSIS +* +* #include "glpnpp.h" +* int npp_make_fixed(NPP *npp, NPPCOL *q); +* +* DESCRIPTION +* +* The routine npp_make_fixed processes column q: +* +* l[q] <= x[q] <= u[q], (1) +* +* where -oo < l[q] < u[q] < +oo, i.e. which has both lower and upper +* bounds. +* +* RETURNS +* +* 0 - column bounds have not been changed; +* +* 1 - column has been fixed. +* +* PROBLEM TRANSFORMATION +* +* If bounds of column (1) are very close to each other: +* +* u[q] - l[q] <= eps, (2) +* +* where eps is an absolute tolerance for column value, the column can +* be fixed: +* +* x[q] = s[q], (3) +* +* where s[q] = (l[q] + u[q]) / 2. And if the fixed column value s[q] +* happens to be very close to its nearest integer: +* +* |s[q] - floor(s[q] + 0.5)| <= eps, (4) +* +* it is reasonable to use this nearest integer as the fixed value. +* +* RECOVERING BASIC SOLUTION +* +* In the dual system of the original (as well as transformed) problem +* column q corresponds to the following row: +* +* sum a[i,q] pi[i] + lambda[q] = c[q]. (5) +* i +* +* Since multipliers pi[i] are known for all rows from solution to the +* transformed problem, formula (5) allows computing value of multiplier +* (reduced cost) for column q: +* +* lambda[q] = c[q] - sum a[i,q] pi[i]. (6) +* i +* +* Status of column q in solution to the original problem is determined +* by its status and the sign of its multiplier lambda[q] in solution to +* the transformed problem as follows: +* +* +-----------------------+-----------+--------------------+ +* | Status of column q | Sign of | Status of column q | +* | (transformed problem) | lambda[q] | (original problem) | +* +-----------------------+-----------+--------------------+ +* | GLP_BS | + / - | GLP_BS | +* | GLP_NS | + | GLP_NL | +* | GLP_NS | - | GLP_NU | +* +-----------------------+-----------+--------------------+ +* +* Value of column q in solution to the original problem is the same as +* in solution to the transformed problem. +* +* RECOVERING INTERIOR POINT SOLUTION +* +* Value of column q in solution to the original problem is the same as +* in solution to the transformed problem. +* +* RECOVERING MIP SOLUTION +* +* None needed. */ + +struct make_fixed +{ /* column with almost identical bounds */ + int q; + /* column reference number */ + double c; + /* objective coefficient at x[q] */ + NPPLFE *ptr; + /* list of non-zero coefficients a[i,q] */ +}; + +static int rcv_make_fixed(NPP *npp, void *info); + +int npp_make_fixed(NPP *npp, NPPCOL *q) +{ /* process column with almost identical bounds */ + struct make_fixed *info; + NPPAIJ *aij; + NPPLFE *lfe; + double s, eps, nint; + /* the column must be double-bounded */ + xassert(q->lb != -DBL_MAX); + xassert(q->ub != +DBL_MAX); + xassert(q->lb < q->ub); + /* check column bounds */ + eps = 1e-9 + 1e-12 * fabs(q->lb); + if (q->ub - q->lb > eps) return 0; + /* column bounds are very close to each other */ + /* create transformation stack entry */ + info = npp_push_tse(npp, + rcv_make_fixed, sizeof(struct make_fixed)); + info->q = q->j; + info->c = q->coef; + info->ptr = NULL; + /* save column coefficients a[i,q] (needed for basic solution + only) */ + if (npp->sol == GLP_SOL) + { for (aij = q->ptr; aij != NULL; aij = aij->c_next) + { lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); + lfe->ref = aij->row->i; + lfe->val = aij->val; + lfe->next = info->ptr; + info->ptr = lfe; + } + } + /* compute column fixed value */ + s = 0.5 * (q->ub + q->lb); + nint = floor(s + 0.5); + if (fabs(s - nint) <= eps) s = nint; + /* make column q fixed */ + q->lb = q->ub = s; + return 1; +} + +static int rcv_make_fixed(NPP *npp, void *_info) +{ /* recover column with almost identical bounds */ + struct make_fixed *info = _info; + NPPLFE *lfe; + double lambda; + if (npp->sol == GLP_SOL) + { if (npp->c_stat[info->q] == GLP_BS) + npp->c_stat[info->q] = GLP_BS; + else if (npp->c_stat[info->q] == GLP_NS) + { /* compute multiplier for column q with formula (6) */ + lambda = info->c; + for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) + lambda -= lfe->val * npp->r_pi[lfe->ref]; + /* assign status to non-basic column */ + if (lambda >= 0.0) + npp->c_stat[info->q] = GLP_NL; + else + npp->c_stat[info->q] = GLP_NU; + } + else + { npp_error(); + return 1; + } + } + return 0; +} + +/* eof */ -- cgit