static PyObject* LPX_basis_adv(LPXObject *self) {
#if GLPK_VERSION(4, 31)
glp_adv_basis(LP, 0);
#else
lpx_adv_basis(LP);
#endif
Py_RETURN_NONE;
}
int c_glp_solve_simplex(glp_prob *lp, int msg_lev, int tm_lim, int presolve){
glp_smcp smcp;
glp_init_smcp (&smcp);
smcp.msg_lev = msg_lev;
smcp.tm_lim = tm_lim;
smcp.presolve = presolve ? GLP_ON : GLP_OFF;
glp_adv_basis(lp, 0);
return glp_simplex(lp, &smcp);
}
int main(void)
{ glp_prob *P;
P = glp_create_prob();
glp_read_mps(P, GLP_MPS_DECK, NULL, "25fv47.mps");
glp_adv_basis(P, 0);
glp_simplex(P, NULL);
glp_print_sol(P, "25fv47.txt");
glp_delete_prob(P);
return 0;
}
static int preprocess_and_solve_mip(glp_prob *P, const glp_iocp *parm)
{ /* solve MIP using the preprocessor */
ENV *env = get_env_ptr();
int term_out = env->term_out;
NPP *npp;
glp_prob *mip = NULL;
glp_bfcp bfcp;
glp_smcp smcp;
int ret;
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("Preprocessing...\n");
/* create preprocessor workspace */
npp = npp_create_wksp();
/* load original problem into the preprocessor workspace */
npp_load_prob(npp, P, GLP_OFF, GLP_MIP, GLP_OFF);
/* process MIP prior to applying the branch-and-bound method */
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
ret = npp_integer(npp, parm);
env->term_out = term_out;
if (ret == 0)
;
else if (ret == GLP_ENOPFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n");
}
else if (ret == GLP_ENODFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("LP RELAXATION HAS NO DUAL FEASIBLE SOLUTION\n");
}
else
xassert(ret != ret);
if (ret != 0) goto done;
/* build transformed MIP */
mip = glp_create_prob();
npp_build_prob(npp, mip);
/* if the transformed MIP is empty, it has empty solution, which
is optimal */
if (mip->m == 0 && mip->n == 0)
{ mip->mip_stat = GLP_OPT;
mip->mip_obj = mip->c0;
if (parm->msg_lev >= GLP_MSG_ALL)
{ xprintf("Objective value = %17.9e\n", mip->mip_obj);
xprintf("INTEGER OPTIMAL SOLUTION FOUND BY MIP PREPROCESSOR"
"\n");
}
goto post;
}
/* display some statistics */
if (parm->msg_lev >= GLP_MSG_ALL)
{ int ni = glp_get_num_int(mip);
int nb = glp_get_num_bin(mip);
char s[50];
xprintf("%d row%s, %d column%s, %d non-zero%s\n",
mip->m, mip->m == 1 ? "" : "s", mip->n, mip->n == 1 ? "" :
"s", mip->nnz, mip->nnz == 1 ? "" : "s");
if (nb == 0)
strcpy(s, "none of");
else if (ni == 1 && nb == 1)
strcpy(s, "");
else if (nb == 1)
strcpy(s, "one of");
else if (nb == ni)
strcpy(s, "all of");
else
sprintf(s, "%d of", nb);
xprintf("%d integer variable%s, %s which %s binary\n",
ni, ni == 1 ? "" : "s", s, nb == 1 ? "is" : "are");
}
/* inherit basis factorization control parameters */
glp_get_bfcp(P, &bfcp);
glp_set_bfcp(mip, &bfcp);
/* scale the transformed problem */
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_scale_prob(mip,
GLP_SF_GM | GLP_SF_EQ | GLP_SF_2N | GLP_SF_SKIP);
env->term_out = term_out;
/* build advanced initial basis */
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_adv_basis(mip, 0);
env->term_out = term_out;
/* solve initial LP relaxation */
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("Solving LP relaxation...\n");
glp_init_smcp(&smcp);
smcp.msg_lev = parm->msg_lev;
mip->it_cnt = P->it_cnt;
ret = glp_simplex(mip, &smcp);
P->it_cnt = mip->it_cnt;
if (ret != 0)
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_intopt: cannot solve LP relaxation\n");
ret = GLP_EFAIL;
goto done;
}
/* check status of the basic solution */
ret = glp_get_status(mip);
if (ret == GLP_OPT)
ret = 0;
else if (ret == GLP_NOFEAS)
ret = GLP_ENOPFS;
else if (ret == GLP_UNBND)
ret = GLP_ENODFS;
else
xassert(ret != ret);
if (ret != 0) goto done;
/* solve the transformed MIP */
mip->it_cnt = P->it_cnt;
#if 0 /* 11/VII-2013 */
ret = solve_mip(mip, parm);
#else
if (parm->use_sol)
{ mip->mip_stat = P->mip_stat;
mip->mip_obj = P->mip_obj;
}
ret = solve_mip(mip, parm, P, npp);
#endif
P->it_cnt = mip->it_cnt;
/* only integer feasible solution can be postprocessed */
if (!(mip->mip_stat == GLP_OPT || mip->mip_stat == GLP_FEAS))
{ P->mip_stat = mip->mip_stat;
goto done;
}
/* postprocess solution from the transformed MIP */
post: npp_postprocess(npp, mip);
/* the transformed MIP is no longer needed */
glp_delete_prob(mip), mip = NULL;
/* store solution to the original problem */
npp_unload_sol(npp, P);
done: /* delete the transformed MIP, if it exists */
if (mip != NULL) glp_delete_prob(mip);
/* delete preprocessor workspace */
npp_delete_wksp(npp);
return ret;
}
char *call_lp(int next_expr(int))
{int i,constraints; expr_type_t goal_type;
char *retval, *retval2;
/* initially the expression to be checked is in entropy_expr.
determine first the variables */
init_var_assignment(); /* start collecting variables */
add_expr_variables(); /* variables in the expression to be checked */
constraints=0;
for(i=0;next_expr(i)==0;i++){ /* go over all constraints */
constraints++;
// Markov constraints give several cols
if(entropy_expr.type==ent_Markov){
constraints+=entropy_expr.n-3;
}
add_expr_variables();
}
/* figure out final variables, rows, cols, number of Shannon */
if(do_variable_assignment()){ // number of variables is less than 2
return "number of final random variables is less than 2";
}
/* get memory for row and column permutation */
cols += constraints;
rowperm=malloc((rows+1)*sizeof(int));
colperm=malloc((cols+1)*sizeof(int));
if(!rowperm || !colperm){
if(rowperm){ free(rowperm); rowperm=NULL; }
if(colperm){ free(colperm); colperm=NULL; }
return "the problem is too large, not enough memory";
}
for(i=0;i<=rows;i++) rowperm[i]=i; perm_array(rows+1,rowperm);
for(i=0;i<=cols;i++) colperm[i]= i-1; perm_array(cols+1,colperm);
/* the expression to be checked, this will be the goal */
if(constraints) next_expr(-1);
goal_type=entropy_expr.type; // ent_eq, ent_ge
create_glp(); // create a new glp instance
for(i=0;i<entropy_expr.n;i++){
row_idx[i+1]=varidx(entropy_expr.item[i].var);
row_val[i+1]=entropy_expr.item[i].coeff;
}
add_goal(entropy_expr.n); // right hand side value
// go over the columns add them to the lp instance
for(i=1;i<=cols;i++){
int colct=colperm[i];
if(add_shannon(i,colct)){ // this is a constraint
add_constraint(i,colct-(shannon+var_no),next_expr);
}
}
/* call the lp */
init_glp_parameters();
if(parm.presolve!=GLP_ON) // generate the first basis
glp_adv_basis(P,0);
retval=invoke_lp();
// call again with -1.0 when checking for ent_eq
if(goal_type==ent_eq && (retval==EXPR_TRUE || retval==EXPR_FALSE)){
next_expr(-1); // reload the problem
for(i=0;i<entropy_expr.n;i++){
row_idx[i+1]=varidx(entropy_expr.item[i].var);
row_val[i+1]=-entropy_expr.item[i].coeff;
}
add_goal(entropy_expr.n); // right hand side value
retval2=invoke_lp();
if(retval2==EXPR_TRUE){
if(retval==EXPR_FALSE) retval=EQ_LE_ONLY;
} else if(retval2==EXPR_FALSE){
if(retval==EXPR_TRUE) retval=EQ_GE_ONLY;
} else {
retval=retval2;
}
}
/* release allocated memory */
release_glp();
if(rowperm){ free(rowperm); rowperm=NULL; }
if(colperm){ free(colperm); colperm=NULL; }
return retval;
}
int max_flow_lp(int nn, int ne, const int beg[/*1+ne*/],
const int end[/*1+ne*/], const int cap[/*1+ne*/], int s, int t,
int x[/*1+ne*/])
{ glp_prob *lp;
glp_smcp smcp;
int i, k, nz, flow, *rn, *cn;
double temp, *aa;
/* create LP problem instance */
lp = glp_create_prob();
/* create LP rows; i-th row is the conservation condition of the
* flow at i-th node, i = 1, ..., nn */
glp_add_rows(lp, nn);
for (i = 1; i <= nn; i++)
glp_set_row_bnds(lp, i, GLP_FX, 0.0, 0.0);
/* create LP columns; k-th column is the elementary flow thru
* k-th edge, k = 1, ..., ne; the last column with the number
* ne+1 is the total flow through the network, which goes along
* a dummy feedback edge from the sink to the source */
glp_add_cols(lp, ne+1);
for (k = 1; k <= ne; k++)
{ xassert(cap[k] > 0);
glp_set_col_bnds(lp, k, GLP_DB, -cap[k], +cap[k]);
}
glp_set_col_bnds(lp, ne+1, GLP_FR, 0.0, 0.0);
/* build the constraint matrix; structurally this matrix is the
* incidence matrix of the network, so each its column (including
* the last column for the dummy edge) has exactly two non-zero
* entries */
rn = xalloc(1+2*(ne+1), sizeof(int));
cn = xalloc(1+2*(ne+1), sizeof(int));
aa = xalloc(1+2*(ne+1), sizeof(double));
nz = 0;
for (k = 1; k <= ne; k++)
{ /* x[k] > 0 means the elementary flow thru k-th edge goes from
* node beg[k] to node end[k] */
nz++, rn[nz] = beg[k], cn[nz] = k, aa[nz] = -1.0;
nz++, rn[nz] = end[k], cn[nz] = k, aa[nz] = +1.0;
}
/* total flow thru the network goes from the sink to the source
* along the dummy feedback edge */
nz++, rn[nz] = t, cn[nz] = ne+1, aa[nz] = -1.0;
nz++, rn[nz] = s, cn[nz] = ne+1, aa[nz] = +1.0;
/* check the number of non-zero entries */
xassert(nz == 2*(ne+1));
/* load the constraint matrix into the LP problem object */
glp_load_matrix(lp, nz, rn, cn, aa);
xfree(rn);
xfree(cn);
xfree(aa);
/* objective function is the total flow through the network to
* be maximized */
glp_set_obj_dir(lp, GLP_MAX);
glp_set_obj_coef(lp, ne + 1, 1.0);
/* solve LP instance with the (primal) simplex method */
glp_term_out(0);
glp_adv_basis(lp, 0);
glp_term_out(1);
glp_init_smcp(&smcp);
smcp.msg_lev = GLP_MSG_ON;
smcp.out_dly = 5000;
xassert(glp_simplex(lp, &smcp) == 0);
xassert(glp_get_status(lp) == GLP_OPT);
/* obtain optimal elementary flows thru edges of the network */
/* (note that the constraint matrix is unimodular and the data
* are integral, so all elementary flows in basic solution should
* also be integral) */
for (k = 1; k <= ne; k++)
{ temp = glp_get_col_prim(lp, k);
x[k] = (int)floor(temp + .5);
xassert(fabs(x[k] - temp) <= 1e-6);
}
/* obtain the maximum flow thru the original network which is the
* flow thru the dummy feedback edge */
temp = glp_get_col_prim(lp, ne+1);
flow = (int)floor(temp + .5);
xassert(fabs(flow - temp) <= 1e-6);
/* delete LP problem instance */
glp_delete_prob(lp);
/* return to the calling program */
return flow;
}
OptSolutionData* GLPKRunSolver(int ProbType) {
OptSolutionData* NewSolution = NULL;
int NumVariables = glp_get_num_cols(GLPKModel);
int Status = 0;
if (ProbType == MILP) {
Status = glp_simplex(GLPKModel, NULL); // Use default settings
if (Status != 0) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
Status = glp_intopt(GLPKModel, NULL); // Use default settings
if (Status != 0) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
NewSolution = new OptSolutionData;
Status = glp_mip_status(GLPKModel);
if (Status == GLP_UNDEF || Status == GLP_NOFEAS) {
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else if (Status == GLP_FEAS) {
NewSolution->Status = UNBOUNDED;
return NewSolution;
} else if (Status == GLP_OPT) {
NewSolution->Status = SUCCESS;
} else {
delete NewSolution;
FErrorFile() << "Problem status unrecognized." << endl;
FlushErrorFile();
return NULL;
}
NewSolution->Objective = glp_mip_obj_val(GLPKModel);
NewSolution->SolutionData.resize(NumVariables);
for (int i=0; i < NumVariables; i++) {
NewSolution->SolutionData[i] = glp_mip_col_val(GLPKModel, i+1);
}
} else if (ProbType == LP) {
//First we check the basis matrix to ensure it is not singular
if (glp_warm_up(GLPKModel) != 0) {
glp_adv_basis(GLPKModel, 0);
}
Status = glp_simplex(GLPKModel, NULL); // Use default settings
if (Status == GLP_EBADB) { /* the basis is invalid; build some valid basis */
glp_adv_basis(GLPKModel, 0);
Status = glp_simplex(GLPKModel, NULL); // Use default settings
}
if (Status != 0) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
NewSolution = new OptSolutionData;
Status = glp_get_status(GLPKModel);
if (Status == GLP_INFEAS || Status == GLP_NOFEAS || Status == GLP_UNDEF) {
cout << "Model is infeasible" << endl;
FErrorFile() << "Model is infeasible" << endl;
FlushErrorFile();
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else if (Status == GLP_FEAS || Status == GLP_UNBND) {
cout << "Model is unbounded" << endl;
FErrorFile() << "Model is unbounded" << endl;
FlushErrorFile();
NewSolution->Status = UNBOUNDED;
return NewSolution;
} else if (Status == GLP_OPT) {
NewSolution->Status = SUCCESS;
} else {
delete NewSolution;
FErrorFile() << "Problem status unrecognized." << endl;
FlushErrorFile();
return NULL;
}
NewSolution->Objective = glp_get_obj_val(GLPKModel);
NewSolution->SolutionData.resize(NumVariables);
for (int i=0; i < NumVariables; i++) {
NewSolution->SolutionData[i] = glp_get_col_prim(GLPKModel, i+1);
}
} else {
FErrorFile() << "Optimization problem type cannot be handled by GLPK solver." << endl;
FlushErrorFile();
return NULL;
}
return NewSolution;
}
void lpx_adv_basis(LPX *lp)
{ /* construct advanced initial LP basis */
glp_adv_basis(lp, 0);
return;
}
static int preprocess_and_solve_lp(glp_prob *P, const glp_smcp *parm)
{ /* solve LP using the preprocessor */
NPP *npp;
glp_prob *lp = NULL;
glp_bfcp bfcp;
int ret;
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("Preprocessing...\n");
/* create preprocessor workspace */
npp = npp_create_wksp();
/* load original problem into the preprocessor workspace */
npp_load_prob(npp, P, GLP_OFF, GLP_SOL, GLP_OFF);
/* process LP prior to applying primal/dual simplex method */
ret = npp_simplex(npp, parm);
if (ret == 0)
;
else if (ret == GLP_ENOPFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n");
}
else if (ret == GLP_ENODFS)
{ if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n");
}
else
xassert(ret != ret);
if (ret != 0) goto done;
/* build transformed LP */
lp = glp_create_prob();
npp_build_prob(npp, lp);
/* if the transformed LP is empty, it has empty solution, which
is optimal */
if (lp->m == 0 && lp->n == 0)
{ lp->pbs_stat = lp->dbs_stat = GLP_FEAS;
lp->obj_val = lp->c0;
if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0)
{ xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt,
lp->obj_val, 0.0);
}
if (parm->msg_lev >= GLP_MSG_ALL)
xprintf("OPTIMAL SOLUTION FOUND BY LP PREPROCESSOR\n");
goto post;
}
if (parm->msg_lev >= GLP_MSG_ALL)
{ xprintf("%d row%s, %d column%s, %d non-zero%s\n",
lp->m, lp->m == 1 ? "" : "s", lp->n, lp->n == 1 ? "" : "s",
lp->nnz, lp->nnz == 1 ? "" : "s");
}
/* inherit basis factorization control parameters */
glp_get_bfcp(P, &bfcp);
glp_set_bfcp(lp, &bfcp);
/* scale the transformed problem */
{ ENV *env = get_env_ptr();
int term_out = env->term_out;
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_scale_prob(lp, GLP_SF_AUTO);
env->term_out = term_out;
}
/* build advanced initial basis */
{ ENV *env = get_env_ptr();
int term_out = env->term_out;
if (!term_out || parm->msg_lev < GLP_MSG_ALL)
env->term_out = GLP_OFF;
else
env->term_out = GLP_ON;
glp_adv_basis(lp, 0);
env->term_out = term_out;
}
/* solve the transformed LP */
lp->it_cnt = P->it_cnt;
ret = solve_lp(lp, parm);
P->it_cnt = lp->it_cnt;
/* only optimal solution can be postprocessed */
if (!(ret == 0 && lp->pbs_stat == GLP_FEAS && lp->dbs_stat ==
GLP_FEAS))
{ if (parm->msg_lev >= GLP_MSG_ERR)
xprintf("glp_simplex: unable to recover undefined or non-op"
"timal solution\n");
if (ret == 0)
{ if (lp->pbs_stat == GLP_NOFEAS)
ret = GLP_ENOPFS;
else if (lp->dbs_stat == GLP_NOFEAS)
ret = GLP_ENODFS;
else
xassert(lp != lp);
}
goto done;
}
post: /* postprocess solution from the transformed LP */
npp_postprocess(npp, lp);
/* the transformed LP is no longer needed */
glp_delete_prob(lp), lp = NULL;
/* store solution to the original problem */
npp_unload_sol(npp, P);
/* the original LP has been successfully solved */
ret = 0;
done: /* delete the transformed LP, if it exists */
if (lp != NULL) glp_delete_prob(lp);
/* delete preprocessor workspace */
npp_delete_wksp(npp);
return ret;
}
int glpk (int sense, int n, int m, double *c, int nz, int *rn, int *cn,
double *a, double *b, char *ctype, int *freeLB, double *lb,
int *freeUB, double *ub, int *vartype, int isMIP, int lpsolver,
int save_pb, char *save_filename, char *filetype,
double *xmin, double *fmin, double *status,
double *lambda, double *redcosts, double *time, double *mem)
{
int typx = 0;
int method;
clock_t t_start = clock();
//Redirect standard output
if (glpIntParam[0] > 1) glp_term_hook (glpk_print_hook, NULL);
else glp_term_hook (NULL, NULL);
//-- Create an empty LP/MILP object
LPX *lp = lpx_create_prob ();
//-- Set the sense of optimization
if (sense == 1)
glp_set_obj_dir (lp, GLP_MIN);
else
glp_set_obj_dir (lp, GLP_MAX);
//-- Define the number of unknowns and their domains.
glp_add_cols (lp, n);
for (int i = 0; i < n; i++)
{
//-- Define type of the structural variables
if (! freeLB[i] && ! freeUB[i]) {
if ( lb[i] == ub[i] )
glp_set_col_bnds (lp, i+1, GLP_FX, lb[i], ub[i]);
else
glp_set_col_bnds (lp, i+1, GLP_DB, lb[i], ub[i]);
}
else
{
if (! freeLB[i] && freeUB[i])
glp_set_col_bnds (lp, i+1, GLP_LO, lb[i], ub[i]);
else
{
if (freeLB[i] && ! freeUB[i])
glp_set_col_bnds (lp, i+1, GLP_UP, lb[i], ub[i]);
else
glp_set_col_bnds (lp, i+1, GLP_FR, lb[i], ub[i]);
}
}
// -- Set the objective coefficient of the corresponding
// -- structural variable. No constant term is assumed.
glp_set_obj_coef(lp,i+1,c[i]);
if (isMIP)
glp_set_col_kind (lp, i+1, vartype[i]);
}
glp_add_rows (lp, m);
for (int i = 0; i < m; i++)
{
/* If the i-th row has no lower bound (types F,U), the
corrispondent parameter will be ignored.
If the i-th row has no upper bound (types F,L), the corrispondent
parameter will be ignored.
If the i-th row is of S type, the i-th LB is used, but
the i-th UB is ignored.
*/
switch (ctype[i])
{
case 'F': typx = GLP_FR; break;
// upper bound
case 'U': typx = GLP_UP; break;
// lower bound
case 'L': typx = GLP_LO; break;
// fixed constraint
case 'S': typx = GLP_FX; break;
// double-bounded variable
case 'D': typx = GLP_DB; break;
}
if ( typx == GLP_DB && -b[i] < b[i]) {
glp_set_row_bnds (lp, i+1, typx, -b[i], b[i]);
}
else if(typx == GLP_DB && -b[i] == b[i]) {
glp_set_row_bnds (lp, i+1, GLP_FX, b[i], b[i]);
}
else {
// this should be glp_set_row_bnds (lp, i+1, typx, -b[i], b[i]);
glp_set_row_bnds (lp, i+1, typx, b[i], b[i]);
}
}
// Load constraint matrix A
glp_load_matrix (lp, nz, rn, cn, a);
// Save problem
if (save_pb) {
if (!strcmp(filetype,"cplex")){
if (glp_write_lp (lp, NULL, save_filename) != 0) {
mexErrMsgTxt("glpk: unable to write the problem");
longjmp (mark, -1);
}
}else{
if (!strcmp(filetype,"fixedmps")){
if (glp_write_mps (lp, GLP_MPS_DECK, NULL, save_filename) != 0) {
mexErrMsgTxt("glpk: unable to write the problem");
longjmp (mark, -1);
}
}else{
if (!strcmp(filetype,"freemps")){
if (glp_write_mps (lp, GLP_MPS_FILE, NULL, save_filename) != 0) {
mexErrMsgTxt("glpk: unable to write the problem");
longjmp (mark, -1);
}
}else{// plain text
if (lpx_print_prob (lp, save_filename) != 0) {
mexErrMsgTxt("glpk: unable to write the problem");
longjmp (mark, -1);
}
}
}
}
}
//-- scale the problem data (if required)
if (! glpIntParam[16] || lpsolver != 1) {
switch ( glpIntParam[1] ) {
case ( 0 ): glp_scale_prob( lp, GLP_SF_SKIP ); break;
case ( 1 ): glp_scale_prob( lp, GLP_SF_GM ); break;
case ( 2 ): glp_scale_prob( lp, GLP_SF_EQ ); break;
case ( 3 ): glp_scale_prob( lp, GLP_SF_AUTO ); break;
case ( 4 ): glp_scale_prob( lp, GLP_SF_2N ); break;
default :
mexErrMsgTxt("glpk: unrecognized scaling option");
longjmp (mark, -1);
}
}
else {
/* do nothing? or unscale?
glp_unscale_prob( lp );
*/
}
//-- build advanced initial basis (if required)
if (lpsolver == 1 && ! glpIntParam[16])
glp_adv_basis (lp, 0);
glp_smcp sParam;
glp_init_smcp(&sParam);
//-- set control parameters for simplex/exact method
if (lpsolver == 1 || lpsolver == 3){
//remap of control parameters for simplex method
sParam.msg_lev=glpIntParam[0]; // message level
// simplex method: primal/dual
switch ( glpIntParam[2] ) {
case 0: sParam.meth=GLP_PRIMAL; break;
case 1: sParam.meth=GLP_DUAL; break;
case 2: sParam.meth=GLP_DUALP; break;
default:
mexErrMsgTxt("glpk: unrecognized primal/dual method");
longjmp (mark, -1);
}
// pricing technique
if (glpIntParam[3]==0) sParam.pricing=GLP_PT_STD;
else sParam.pricing=GLP_PT_PSE;
// ratio test
if (glpIntParam[20]==0) sParam.r_test = GLP_RT_STD;
else sParam.r_test=GLP_RT_HAR;
//tollerances
sParam.tol_bnd=glpRealParam[1]; // primal feasible tollerance
sParam.tol_dj=glpRealParam[2]; // dual feasible tollerance
sParam.tol_piv=glpRealParam[3]; // pivot tollerance
sParam.obj_ll=glpRealParam[4]; // lower limit
sParam.obj_ul=glpRealParam[5]; // upper limit
// iteration limit
if (glpIntParam[5]==-1) sParam.it_lim=INT_MAX;
else sParam.it_lim=glpIntParam[5];
// time limit
if (glpRealParam[6]==-1) sParam.tm_lim=INT_MAX;
else sParam.tm_lim=(int) glpRealParam[6];
sParam.out_frq=glpIntParam[7]; // output frequency
sParam.out_dly=(int) glpRealParam[7]; // output delay
// presolver
if (glpIntParam[16]) sParam.presolve=GLP_ON;
else sParam.presolve=GLP_OFF;
}else{
for(int i = 0; i < NIntP; i++) {
// skip assinging ratio test or
if ( i == 18 || i == 20) continue;
lpx_set_int_parm (lp, IParam[i], glpIntParam[i]);
}
for (int i = 0; i < NRealP; i++) {
lpx_set_real_parm (lp, RParam[i], glpRealParam[i]);
}
}
//set MIP params if MIP....
glp_iocp iParam;
glp_init_iocp(&iParam);
if ( isMIP ){
method = 'I';
switch (glpIntParam[0]) { //message level
case 0: iParam.msg_lev = GLP_MSG_OFF; break;
case 1: iParam.msg_lev = GLP_MSG_ERR; break;
case 2: iParam.msg_lev = GLP_MSG_ON; break;
case 3: iParam.msg_lev = GLP_MSG_ALL; break;
default: mexErrMsgTxt("glpk: msg_lev bad param");
}
switch (glpIntParam[14]) { //branching param
case 0: iParam.br_tech = GLP_BR_FFV; break;
case 1: iParam.br_tech = GLP_BR_LFV; break;
case 2: iParam.br_tech = GLP_BR_MFV; break;
case 3: iParam.br_tech = GLP_BR_DTH; break;
default: mexErrMsgTxt("glpk: branch bad param");
}
switch (glpIntParam[15]) { //backtracking heuristic
case 0: iParam.bt_tech = GLP_BT_DFS; break;
case 1: iParam.bt_tech = GLP_BT_BFS; break;
case 2: iParam.bt_tech = GLP_BT_BLB; break;
case 3: iParam.bt_tech = GLP_BT_BPH; break;
default: mexErrMsgTxt("glpk: backtrack bad param");
}
if ( glpRealParam[8] > 0.0 && glpRealParam[8] < 1.0 )
iParam.tol_int = glpRealParam[8]; // absolute tolorence
else
mexErrMsgTxt("glpk: tolint must be between 0 and 1");
iParam.tol_obj = glpRealParam[9]; // relative tolarence
iParam.mip_gap = glpRealParam[10]; // realative gap tolerance
// set time limit for mip
if ( glpRealParam[6] < 0.0 || glpRealParam[6] > 1e6 )
iParam.tm_lim = INT_MAX;
else
iParam.tm_lim = (int)(1000.0 * glpRealParam[6] );
// Choose Cutsets for mip
// shut all cuts off, then start over....
iParam.gmi_cuts = GLP_OFF;
iParam.mir_cuts = GLP_OFF;
iParam.cov_cuts = GLP_OFF;
iParam.clq_cuts = GLP_OFF;
switch( glpIntParam[17] ) {
case 0: break;
case 1: iParam.gmi_cuts = GLP_ON; break;
case 2: iParam.mir_cuts = GLP_ON; break;
case 3: iParam.cov_cuts = GLP_ON; break;
case 4: iParam.clq_cuts = GLP_ON; break;
case 5: iParam.clq_cuts = GLP_ON;
iParam.gmi_cuts = GLP_ON;
iParam.mir_cuts = GLP_ON;
iParam.cov_cuts = GLP_ON;
iParam.clq_cuts = GLP_ON; break;
default: mexErrMsgTxt("glpk: cutset bad param");
}
switch( glpIntParam[18] ) { // pre-processing for mip
case 0: iParam.pp_tech = GLP_PP_NONE; break;
case 1: iParam.pp_tech = GLP_PP_ROOT; break;
case 2: iParam.pp_tech = GLP_PP_ALL; break;
default: mexErrMsgTxt("glpk: pprocess bad param");
}
if (glpIntParam[16]) iParam.presolve=GLP_ON;
else iParam.presolve=GLP_OFF;
if (glpIntParam[19]) iParam.binarize = GLP_ON;
else iParam.binarize = GLP_OFF;
}
else {
/* Choose simplex method ('S')
or interior point method ('T')
or Exact method ('E')
to solve the problem */
switch (lpsolver) {
case 1: method = 'S'; break;
case 2: method = 'T'; break;
case 3: method = 'E'; break;
default:
mexErrMsgTxt("glpk: lpsolver != lpsolver");
longjmp (mark, -1);
}
}
// now run the problem...
int errnum = 0;
switch (method) {
case 'I':
errnum = glp_intopt( lp, &iParam );
errnum += 200; //this is to avoid ambiguity in the return codes.
break;
case 'S':
errnum = glp_simplex(lp, &sParam);
errnum += 100; //this is to avoid ambiguity in the return codes.
break;
case 'T':
errnum = glp_interior(lp, NULL );
errnum += 300; //this is to avoid ambiguity in the return codes.
break;
case 'E':
errnum = glp_exact(lp, &sParam);
errnum += 100; //this is to avoid ambiguity in the return codes.
break;
default: /*xassert (method != method); */
mexErrMsgTxt("glpk: method != method");
longjmp (mark, -1);
}
if (errnum==100 || errnum==200 || errnum==300 || errnum==106 || errnum==107 || errnum==108 || errnum==109 || errnum==209 || errnum==214 || errnum==308) {
// Get status and object value
if (isMIP) {
*status = glp_mip_status (lp);
*fmin = glp_mip_obj_val (lp);
}
else {
if (lpsolver == 1 || lpsolver == 3) {
*status = glp_get_status (lp);
*fmin = glp_get_obj_val (lp);
}
else {
*status = glp_ipt_status (lp);
*fmin = glp_ipt_obj_val (lp);
}
}
// Get optimal solution (if exists)
if (isMIP) {
for (int i = 0; i < n; i++)
xmin[i] = glp_mip_col_val (lp, i+1);
}
else {
/* Primal values */
for (int i = 0; i < n; i++) {
if (lpsolver == 1 || lpsolver == 3)
xmin[i] = glp_get_col_prim (lp, i+1);
else
xmin[i] = glp_ipt_col_prim (lp, i+1);
}
/* Dual values */
for (int i = 0; i < m; i++) {
if (lpsolver == 1 || lpsolver == 3)
lambda[i] = glp_get_row_dual (lp, i+1);
else
lambda[i] = glp_ipt_row_dual (lp, i+1);
}
/* Reduced costs */
for (int i = 0; i < glp_get_num_cols (lp); i++) {
if (lpsolver == 1 || lpsolver == 3)
redcosts[i] = glp_get_col_dual (lp, i+1);
else
redcosts[i] = glp_ipt_col_dual (lp, i+1);
}
}
*time = (clock () - t_start) / CLOCKS_PER_SEC;
size_t tpeak;
glp_mem_usage(NULL, NULL, NULL, &tpeak);
*mem=((double) tpeak) / (1024);
lpx_delete_prob(lp);
return 0;
}
else {
// printf("errnum is %d\n", errnum);
}
lpx_delete_prob(lp);
/* this shouldn't be nessiary with glp_deleted_prob, but try it
if we have weird behavior again... */
glp_free_env();
*status = errnum;
return errnum;
}
int glp_main(int argc, const char *argv[])
{ /* stand-alone LP/MIP solver */
struct csa _csa, *csa = &_csa;
int ret;
xlong_t start;
/* perform initialization */
csa->prob = glp_create_prob();
glp_get_bfcp(csa->prob, &csa->bfcp);
glp_init_smcp(&csa->smcp);
csa->smcp.presolve = GLP_ON;
glp_init_iocp(&csa->iocp);
csa->iocp.presolve = GLP_ON;
csa->tran = NULL;
csa->graph = NULL;
csa->format = FMT_MPS_FILE;
csa->in_file = NULL;
csa->ndf = 0;
csa->out_dpy = NULL;
csa->solution = SOL_BASIC;
csa->in_res = NULL;
csa->dir = 0;
csa->scale = 1;
csa->out_sol = NULL;
csa->out_res = NULL;
csa->out_bnds = NULL;
csa->check = 0;
csa->new_name = NULL;
csa->out_mps = NULL;
csa->out_freemps = NULL;
csa->out_cpxlp = NULL;
csa->out_pb = NULL;
csa->out_npb = NULL;
csa->log_file = NULL;
csa->crash = USE_ADV_BASIS;
csa->exact = 0;
csa->xcheck = 0;
csa->nomip = 0;
/* parse command-line parameters */
ret = parse_cmdline(csa, argc, argv);
if (ret < 0)
{ ret = EXIT_SUCCESS;
goto done;
}
if (ret > 0)
{ ret = EXIT_FAILURE;
goto done;
}
/*--------------------------------------------------------------*/
/* remove all output files specified in the command line */
if (csa->out_dpy != NULL) remove(csa->out_dpy);
if (csa->out_sol != NULL) remove(csa->out_sol);
if (csa->out_res != NULL) remove(csa->out_res);
if (csa->out_bnds != NULL) remove(csa->out_bnds);
if (csa->out_mps != NULL) remove(csa->out_mps);
if (csa->out_freemps != NULL) remove(csa->out_freemps);
if (csa->out_cpxlp != NULL) remove(csa->out_cpxlp);
if (csa->out_pb != NULL) remove(csa->out_pb);
if (csa->out_npb != NULL) remove(csa->out_npb);
if (csa->log_file != NULL) remove(csa->log_file);
/*--------------------------------------------------------------*/
/* open log file, if required */
if (csa->log_file != NULL)
{ if (lib_open_log(csa->log_file))
{ xprintf("Unable to create log file\n");
ret = EXIT_FAILURE;
goto done;
}
}
/*--------------------------------------------------------------*/
/* read problem data from the input file */
if (csa->in_file == NULL)
{ xprintf("No input problem file specified; try %s --help\n",
argv[0]);
ret = EXIT_FAILURE;
goto done;
}
if (csa->format == FMT_MPS_DECK)
{ ret = glp_read_mps(csa->prob, GLP_MPS_DECK, NULL,
csa->in_file);
if (ret != 0)
err1: { xprintf("MPS file processing error\n");
ret = EXIT_FAILURE;
goto done;
}
}
else if (csa->format == FMT_MPS_FILE)
{ ret = glp_read_mps(csa->prob, GLP_MPS_FILE, NULL,
csa->in_file);
if (ret != 0) goto err1;
}
else if (csa->format == FMT_CPLEX_LP)
{ ret = glp_read_lp(csa->prob, NULL, csa->in_file);
if (ret != 0)
{ xprintf("CPLEX LP file processing error\n");
ret = EXIT_FAILURE;
goto done;
}
}
else if (csa->format == FMT_MATHPROG)
{ int k;
/* allocate the translator workspace */
csa->tran = glp_mpl_alloc_wksp();
/* read model section and optional data section */
if (glp_mpl_read_model(csa->tran, csa->in_file, csa->ndf > 0))
err2: { xprintf("MathProg model processing error\n");
ret = EXIT_FAILURE;
goto done;
}
/* read optional data section(s), if necessary */
for (k = 1; k <= csa->ndf; k++)
{ if (glp_mpl_read_data(csa->tran, csa->in_data[k]))
goto err2;
}
/* generate the model */
if (glp_mpl_generate(csa->tran, csa->out_dpy)) goto err2;
/* build the problem instance from the model */
glp_mpl_build_prob(csa->tran, csa->prob);
}
else if (csa->format == FMT_MIN_COST)
{ csa->graph = glp_create_graph(sizeof(v_data), sizeof(a_data));
ret = glp_read_mincost(csa->graph, offsetof(v_data, rhs),
offsetof(a_data, low), offsetof(a_data, cap),
offsetof(a_data, cost), csa->in_file);
if (ret != 0)
{ xprintf("DIMACS file processing error\n");
ret = EXIT_FAILURE;
goto done;
}
glp_mincost_lp(csa->prob, csa->graph, GLP_ON,
offsetof(v_data, rhs), offsetof(a_data, low),
offsetof(a_data, cap), offsetof(a_data, cost));
glp_set_prob_name(csa->prob, csa->in_file);
}
else if (csa->format == FMT_MAX_FLOW)
{ int s, t;
csa->graph = glp_create_graph(sizeof(v_data), sizeof(a_data));
ret = glp_read_maxflow(csa->graph, &s, &t,
offsetof(a_data, cap), csa->in_file);
if (ret != 0)
{ xprintf("DIMACS file processing error\n");
ret = EXIT_FAILURE;
goto done;
}
glp_maxflow_lp(csa->prob, csa->graph, GLP_ON, s, t,
offsetof(a_data, cap));
glp_set_prob_name(csa->prob, csa->in_file);
}
else
xassert(csa != csa);
/*--------------------------------------------------------------*/
/* change problem name, if required */
if (csa->new_name != NULL)
glp_set_prob_name(csa->prob, csa->new_name);
/* change optimization direction, if required */
if (csa->dir != 0)
glp_set_obj_dir(csa->prob, csa->dir);
/* order rows and columns of the constraint matrix */
lpx_order_matrix(csa->prob);
/*--------------------------------------------------------------*/
/* write problem data in fixed MPS format, if required */
if (csa->out_mps != NULL)
{ ret = glp_write_mps(csa->prob, GLP_MPS_DECK, NULL,
csa->out_mps);
if (ret != 0)
{ xprintf("Unable to write problem in fixed MPS format\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write problem data in free MPS format, if required */
if (csa->out_freemps != NULL)
{ ret = glp_write_mps(csa->prob, GLP_MPS_FILE, NULL,
csa->out_freemps);
if (ret != 0)
{ xprintf("Unable to write problem in free MPS format\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write problem data in CPLEX LP format, if required */
if (csa->out_cpxlp != NULL)
{ ret = glp_write_lp(csa->prob, NULL, csa->out_cpxlp);
if (ret != 0)
{ xprintf("Unable to write problem in CPLEX LP format\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write problem data in OPB format, if required */
if (csa->out_pb != NULL)
{ ret = lpx_write_pb(csa->prob, csa->out_pb, 0, 0);
if (ret != 0)
{ xprintf("Unable to write problem in OPB format\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write problem data in normalized OPB format, if required */
if (csa->out_npb != NULL)
{ ret = lpx_write_pb(csa->prob, csa->out_npb, 1, 1);
if (ret != 0)
{ xprintf(
"Unable to write problem in normalized OPB format\n");
ret = EXIT_FAILURE;
goto done;
}
}
/*--------------------------------------------------------------*/
/* if only problem data check is required, skip computations */
if (csa->check)
{ ret = EXIT_SUCCESS;
goto done;
}
/*--------------------------------------------------------------*/
/* determine the solution type */
if (!csa->nomip &&
glp_get_num_int(csa->prob) + glp_get_num_bin(csa->prob) > 0)
{ if (csa->solution == SOL_INTERIOR)
{ xprintf("Interior-point method is not able to solve MIP pro"
"blem; use --simplex\n");
ret = EXIT_FAILURE;
goto done;
}
csa->solution = SOL_INTEGER;
}
/*--------------------------------------------------------------*/
/* if solution is provided, read it and skip computations */
if (csa->in_res != NULL)
{ if (csa->solution == SOL_BASIC)
ret = glp_read_sol(csa->prob, csa->in_res);
else if (csa->solution == SOL_INTERIOR)
ret = glp_read_ipt(csa->prob, csa->in_res);
else if (csa->solution == SOL_INTEGER)
ret = glp_read_mip(csa->prob, csa->in_res);
else
xassert(csa != csa);
if (ret != 0)
{ xprintf("Unable to read problem solution\n");
ret = EXIT_FAILURE;
goto done;
}
goto skip;
}
/*--------------------------------------------------------------*/
/* scale the problem data, if required */
if (csa->scale)
{ if (csa->solution == SOL_BASIC && !csa->smcp.presolve ||
csa->solution == SOL_INTERIOR ||
csa->solution == SOL_INTEGER && !csa->iocp.presolve)
glp_scale_prob(csa->prob, GLP_SF_AUTO);
}
/* construct starting LP basis */
if (csa->solution == SOL_BASIC && !csa->smcp.presolve ||
csa->solution == SOL_INTEGER && !csa->iocp.presolve)
{ if (csa->crash == USE_STD_BASIS)
glp_std_basis(csa->prob);
else if (csa->crash == USE_ADV_BASIS)
glp_adv_basis(csa->prob, 0);
else if (csa->crash == USE_CPX_BASIS)
glp_cpx_basis(csa->prob);
else
xassert(csa != csa);
}
/*--------------------------------------------------------------*/
/* solve the problem */
start = xtime();
if (csa->solution == SOL_BASIC)
{ if (!csa->exact)
{ glp_set_bfcp(csa->prob, &csa->bfcp);
glp_simplex(csa->prob, &csa->smcp);
if (csa->xcheck)
{ if (csa->smcp.presolve &&
glp_get_status(csa->prob) != GLP_OPT)
xprintf("If you need to check final basis for non-opt"
"imal solution, use --nopresol\n");
else
glp_exact(csa->prob, &csa->smcp);
}
if (csa->out_sol != NULL || csa->out_res != NULL)
{ if (csa->smcp.presolve &&
glp_get_status(csa->prob) != GLP_OPT)
xprintf("If you need actual output for non-optimal solut"
"ion, use --nopresol\n");
}
}
else
glp_exact(csa->prob, &csa->smcp);
}
else if (csa->solution == SOL_INTERIOR)
glp_interior(csa->prob, NULL);
else if (csa->solution == SOL_INTEGER)
{ if (!csa->iocp.presolve)
{ glp_set_bfcp(csa->prob, &csa->bfcp);
glp_simplex(csa->prob, &csa->smcp);
}
glp_intopt(csa->prob, &csa->iocp);
}
else
xassert(csa != csa);
/*--------------------------------------------------------------*/
/* display statistics */
xprintf("Time used: %.1f secs\n", xdifftime(xtime(), start));
{ xlong_t tpeak;
char buf[50];
lib_mem_usage(NULL, NULL, NULL, &tpeak);
xprintf("Memory used: %.1f Mb (%s bytes)\n",
xltod(tpeak) / 1048576.0, xltoa(tpeak, buf));
}
/*--------------------------------------------------------------*/
skip: /* postsolve the model, if necessary */
if (csa->tran != NULL)
{ if (csa->solution == SOL_BASIC)
ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_SOL);
else if (csa->solution == SOL_INTERIOR)
ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_IPT);
else if (csa->solution == SOL_INTEGER)
ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_MIP);
else
xassert(csa != csa);
if (ret != 0)
{ xprintf("Model postsolving error\n");
ret = EXIT_FAILURE;
goto done;
}
}
/*--------------------------------------------------------------*/
/* write problem solution in printable format, if required */
if (csa->out_sol != NULL)
{ if (csa->solution == SOL_BASIC)
ret = lpx_print_sol(csa->prob, csa->out_sol);
else if (csa->solution == SOL_INTERIOR)
ret = lpx_print_ips(csa->prob, csa->out_sol);
else if (csa->solution == SOL_INTEGER)
ret = lpx_print_mip(csa->prob, csa->out_sol);
else
xassert(csa != csa);
if (ret != 0)
{ xprintf("Unable to write problem solution\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write problem solution in printable format, if required */
if (csa->out_res != NULL)
{ if (csa->solution == SOL_BASIC)
ret = glp_write_sol(csa->prob, csa->out_res);
else if (csa->solution == SOL_INTERIOR)
ret = glp_write_ipt(csa->prob, csa->out_res);
else if (csa->solution == SOL_INTEGER)
ret = glp_write_mip(csa->prob, csa->out_res);
else
xassert(csa != csa);
if (ret != 0)
{ xprintf("Unable to write problem solution\n");
ret = EXIT_FAILURE;
goto done;
}
}
/* write sensitivity bounds information, if required */
if (csa->out_bnds != NULL)
{ if (csa->solution == SOL_BASIC)
{ ret = lpx_print_sens_bnds(csa->prob, csa->out_bnds);
if (ret != 0)
{ xprintf("Unable to write sensitivity bounds information "
"\n");
ret = EXIT_FAILURE;
goto done;
}
}
else
xprintf("Cannot write sensitivity bounds information for in"
"terior-point or MIP solution\n");
}
/*--------------------------------------------------------------*/
/* all seems to be ok */
ret = EXIT_SUCCESS;
/*--------------------------------------------------------------*/
done: /* delete the LP/MIP problem object */
if (csa->prob != NULL)
glp_delete_prob(csa->prob);
/* free the translator workspace, if necessary */
if (csa->tran != NULL)
glp_mpl_free_wksp(csa->tran);
/* delete the network problem object, if necessary */
if (csa->graph != NULL)
glp_delete_graph(csa->graph);
xassert(gmp_pool_count() == 0);
gmp_free_mem();
/* close log file, if necessary */
if (csa->log_file != NULL) lib_close_log();
/* check that no memory blocks are still allocated */
{ int count;
xlong_t total;
lib_mem_usage(&count, NULL, &total, NULL);
if (count != 0)
xerror("Error: %d memory block(s) were lost\n", count);
xassert(count == 0);
xassert(total.lo == 0 && total.hi == 0);
}
/* free the library environment */
lib_free_env();
/* return to the control program */
return ret;
}