int CClp_opt(CClp *lp, int method)
{ /* CALLS designated LP solution method. */
int stat, ret;
if (MSGLEV >= 1)
{ int m = lpx_get_num_rows(lp->lp);
int n = lpx_get_num_cols(lp->lp);
int nz = lpx_get_num_nz(lp->lp);
print("CClp_opt: %-11s m = %d; n = %d; nz = %d",
method == CClp_METHOD_DUAL ? "(dual)" : "(primal)",
m, n, nz);
}
lpx_set_int_parm(lp->lp, LPX_K_DUAL, method == CClp_METHOD_DUAL);
switch (MSGLEV)
{ case 0:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 0);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 1000000);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 1e6);
break;
case 1:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 2);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 200);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 5.0);
break;
case 2:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 3);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 200);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 0.0);
break;
default:
insist(MSGLEV != MSGLEV);
}
ret = lpx_simplex(lp->lp);
if (ret == LPX_E_FAULT)
{ if (MSGLEV >= 1) print("CClp_opt: restarting from advanced bas"
"is...");
lpx_adv_basis(lp->lp);
ret = lpx_simplex(lp->lp);
}
if (ret != LPX_E_OK)
{ print("CClp_opt: lpx_simplex failed; return code = %d", ret);
ret = 1;
goto done;
}
stat = lpx_get_status(lp->lp);
if (stat == LPX_OPT)
ret = 0;
else if (stat == LPX_NOFEAS)
ret = 2;
else
{ print("CClp_opt: optimization status = %d", stat);
ret = 1;
}
done: return ret;
}
int main(int argc, char *argv[])
{ LPX *lp;
MPL *mpl = NULL;
int ret;
double start;
/* parse command line parameters */
parse_cmdline(argc, argv);
/* remove all output files specified in the command line */
if (display != NULL) remove(display);
if (out_sol != NULL) remove(out_sol);
if (out_bnds != NULL) remove(out_bnds);
if (out_mps != NULL) remove(out_mps);
if (out_lpt != NULL) remove(out_lpt);
if (out_txt != NULL) remove(out_txt);
if (out_glp != NULL) remove(out_glp);
/* read problem from the input file */
if (in_file == NULL)
{ print("No input file specified; try %s --help", argv[0]);
exit(EXIT_FAILURE);
}
switch (format)
{ case 0:
lp = lpx_read_mps(in_file);
if (lp == NULL)
{ print("MPS file processing error");
exit(EXIT_FAILURE);
}
break;
case 1:
lp = lpx_read_lpt(in_file);
if (lp == NULL)
{ print("CPLEX LP file processing error");
exit(EXIT_FAILURE);
}
break;
case 2:
#if 0 /* 01/VIII-2004 */
lp = lpx_read_model(in_file, in_data, display);
if (lp == NULL)
{ print("Model processing error");
exit(EXIT_FAILURE);
}
#else
/* initialize the translator database */
mpl = mpl_initialize();
/* read model section and optional data section */
ret = mpl_read_model(mpl, in_file, in_data != NULL);
if (ret == 4)
err: { print("Model processing error");
exit(EXIT_FAILURE);
}
insist(ret == 1 || ret == 2);
/* read data section, if necessary */
if (in_data != NULL)
{ insist(ret == 1);
ret = mpl_read_data(mpl, in_data);
if (ret == 4) goto err;
insist(ret == 2);
}
/* generate model */
ret = mpl_generate(mpl, display);
if (ret == 4) goto err;
/* extract problem instance */
lp = lpx_extract_prob(mpl);
insist(lp != NULL);
#endif
if (lpx_get_num_rows(lp) == 0)
{ print("Problem has no rows");
exit(EXIT_FAILURE);
}
if (lpx_get_num_cols(lp) == 0)
{ print("Problem has no columns");
exit(EXIT_FAILURE);
}
break;
case 3:
lp = lpx_read_prob(in_file);
if (lp == NULL)
{ print("GNU LP file processing error");
exit(EXIT_FAILURE);
}
break;
default:
insist(format != format);
}
/* change problem name (if required) */
if (newname != NULL) lpx_set_prob_name(lp, newname);
/* change optimization direction (if required) */
if (dir != 0) lpx_set_obj_dir(lp, dir);
/* write problem in MPS format (if required) */
if (out_mps != NULL)
{ lpx_set_int_parm(lp, LPX_K_MPSORIG, orig);
ret = lpx_write_mps(lp, out_mps);
if (ret != 0)
{ print("Unable to write problem in MPS format");
exit(EXIT_FAILURE);
}
}
/* write problem in CPLEX LP format (if required) */
if (out_lpt != NULL)
{ lpx_set_int_parm(lp, LPX_K_LPTORIG, orig);
ret = lpx_write_lpt(lp, out_lpt);
if (ret != 0)
{ print("Unable to write problem in CPLEX LP format");
exit(EXIT_FAILURE);
}
}
/* write problem in plain text format (if required) */
if (out_txt != NULL)
{ lpx_set_int_parm(lp, LPX_K_LPTORIG, orig);
ret = lpx_print_prob(lp, out_txt);
if (ret != 0)
{ print("Unable to write problem in plain text format");
exit(EXIT_FAILURE);
}
}
/* write problem in GNU LP format (if required) */
if (out_glp != NULL)
{ ret = lpx_write_prob(lp, out_glp);
if (ret != 0)
{ print("Unable to write problem in GNU LP format");
exit(EXIT_FAILURE);
}
}
/* if only data check is required, skip computations */
if (check) goto skip;
/* scale the problem data (if required) */
if (scale && (!presol || method == 1)) lpx_scale_prob(lp);
/* build advanced initial basis (if required) */
if (method == 0 && basis && !presol) lpx_adv_basis(lp);
/* set some control parameters, which might be changed in the
command line */
lpx_set_int_parm(lp, LPX_K_PRICE, price);
if (!relax) lpx_set_real_parm(lp, LPX_K_RELAX, 0.0);
lpx_set_int_parm(lp, LPX_K_PRESOL, presol);
lpx_set_int_parm(lp, LPX_K_BRANCH, branch);
lpx_set_int_parm(lp, LPX_K_BTRACK, btrack);
lpx_set_real_parm(lp, LPX_K_TMLIM, (double)tmlim);
/* solve the problem */
start = utime();
switch (method)
{ case 0:
if (nomip || lpx_get_class(lp) == LPX_LP)
{ ret = lpx_simplex(lp);
if (presol && ret != LPX_E_OK && out_sol != NULL)
print("If you need actual output for non-optimal solu"
"tion, use --nopresol");
}
else
{ method = 2;
lpx_simplex(lp);
if (!intopt)
lpx_integer(lp);
else
lpx_intopt(lp);
}
break;
case 1:
if (nomip || lpx_get_class(lp) == LPX_LP)
lpx_interior(lp);
else
{ print("Interior point method is not able to solve MIP pr"
"oblem; use --simplex");
exit(EXIT_FAILURE);
}
break;
default:
insist(method != method);
}
/* display statistics */
print("Time used: %.1f secs", utime() - start);
print("Memory used: %.1fM (%d bytes)",
(double)lib_env_ptr()->mem_tpeak / (double)(1024 * 1024),
lib_env_ptr()->mem_tpeak);
#if 1 /* 01/VIII-2004 */
if (mpl != NULL && mpl_has_solve_stmt(mpl))
{ int n, j, round;
/* store the solution to the translator database */
n = lpx_get_num_cols(lp);
round = lpx_get_int_parm(lp, LPX_K_ROUND);
lpx_set_int_parm(lp, LPX_K_ROUND, 1);
switch (method)
{ case 0:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_get_col_prim(lp, j));
break;
case 1:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_ipt_col_prim(lp, j));
break;
case 2:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_mip_col_val(lp, j));
break;
default:
insist(method != method);
}
lpx_set_int_parm(lp, LPX_K_ROUND, round);
/* perform postsolving */
ret = mpl_postsolve(mpl, display);
if (ret == 4)
{ print("Model postsolving error");
exit(EXIT_FAILURE);
}
insist(ret == 3);
}
#endif
/* write problem solution found by the solver (if required) */
if (out_sol != NULL)
{ switch (method)
{ case 0:
ret = lpx_print_sol(lp, out_sol);
break;
case 1:
ret = lpx_print_ips(lp, out_sol);
break;
case 2:
ret = lpx_print_mip(lp, out_sol);
break;
default:
insist(method != method);
}
if (ret != 0)
{ print("Unable to write problem solution");
exit(EXIT_FAILURE);
}
}
/* write sensitivity bounds information (if required) */
if (out_bnds != NULL)
{ if (method != 0)
{ print("Cannot write sensitivity bounds information for inte"
"rior-point or MIP solution");
exit(EXIT_FAILURE);
}
ret = lpx_print_sens_bnds(lp, out_bnds);
if (ret != 0)
{ print("Unable to write sensitivity bounds information");
exit(EXIT_FAILURE);
}
}
skip: /* delete the problem object */
lpx_delete_prob(lp);
#if 1 /* 01/VIII-2004 */
/* if the translator database exists, destroy it */
if (mpl != NULL) mpl_terminate(mpl);
#endif
/* check that no memory blocks are still allocated */
insist(lib_env_ptr()->mem_total == 0);
insist(lib_env_ptr()->mem_count == 0);
/* return to the control program */
return 0;
}
int main(int argc, char *argv[])
{ LPX *lp;
MPL *mpl = NULL;
int ret;
ulong_t start;
/* parse command line parameters */
parse_cmdline(argc, argv);
/* set available memory limit */
if (memlim >= 0)
lib_mem_limit(ulmul(ulset(0, 1048576), ulset(0, memlim)));
/* remove all output files specified in the command line */
if (display != NULL) remove(display);
if (out_bas != NULL) remove(out_bas);
if (out_sol != NULL) remove(out_sol);
if (out_bnds != NULL) remove(out_bnds);
if (out_mps != NULL) remove(out_mps);
if (out_freemps != NULL) remove(out_freemps);
if (out_cpxlp != NULL) remove(out_cpxlp);
if (out_txt != NULL) remove(out_txt);
if (out_glp != NULL) remove(out_glp);
if (log_file != NULL) remove(log_file);
/* open hardcopy file, if necessary */
if (log_file != NULL)
{ if (lib_open_log(log_file))
{ print("Unable to create log file");
exit(EXIT_FAILURE);
}
}
/* read problem data from the input file */
if (in_file == NULL)
{ print("No input file specified; try %s --help", argv[0]);
exit(EXIT_FAILURE);
}
switch (format)
{ case 0:
lp = lpx_read_mps(in_file);
if (lp == NULL)
{ print("MPS file processing error");
exit(EXIT_FAILURE);
}
orig = 1;
break;
case 1:
lp = lpx_read_cpxlp(in_file);
if (lp == NULL)
{ print("CPLEX LP file processing error");
exit(EXIT_FAILURE);
}
break;
case 2:
/* initialize the translator database */
mpl = mpl_initialize();
/* read model section and optional data section */
ret = mpl_read_model(mpl, in_file, in_data != NULL);
if (ret == 4)
err: { print("Model processing error");
exit(EXIT_FAILURE);
}
xassert(ret == 1 || ret == 2);
/* read data section, if necessary */
if (in_data != NULL)
{ xassert(ret == 1);
ret = mpl_read_data(mpl, in_data);
if (ret == 4) goto err;
xassert(ret == 2);
}
/* generate model */
ret = mpl_generate(mpl, display);
if (ret == 4) goto err;
/* extract problem instance */
lp = lpx_extract_prob(mpl);
xassert(lp != NULL);
break;
case 3:
lp = lpx_read_prob(in_file);
if (lp == NULL)
{ print("GNU LP file processing error");
exit(EXIT_FAILURE);
}
break;
case 4:
lp = lpx_read_freemps(in_file);
if (lp == NULL)
{ print("MPS file processing error");
exit(EXIT_FAILURE);
}
break;
default:
xassert(format != format);
}
/* order rows and columns of the constraint matrix */
lpx_order_matrix(lp);
/* change problem name (if required) */
if (newname != NULL) lpx_set_prob_name(lp, newname);
/* change optimization direction (if required) */
if (dir != 0) lpx_set_obj_dir(lp, dir);
/* write problem in fixed MPS format (if required) */
if (out_mps != NULL)
{ lpx_set_int_parm(lp, LPX_K_MPSORIG, orig);
ret = lpx_write_mps(lp, out_mps);
if (ret != 0)
{ print("Unable to write problem in fixed MPS format");
exit(EXIT_FAILURE);
}
}
/* write problem in free MPS format (if required) */
if (out_freemps != NULL)
{ ret = lpx_write_freemps(lp, out_freemps);
if (ret != 0)
{ print("Unable to write problem in free MPS format");
exit(EXIT_FAILURE);
}
}
/* write problem in CPLEX LP format (if required) */
if (out_cpxlp != NULL)
{ ret = lpx_write_cpxlp(lp, out_cpxlp);
if (ret != 0)
{ print("Unable to write problem in CPLEX LP format");
exit(EXIT_FAILURE);
}
}
/* write problem in plain text format (if required) */
if (out_txt != NULL)
{ lpx_set_int_parm(lp, LPX_K_LPTORIG, orig);
ret = lpx_print_prob(lp, out_txt);
if (ret != 0)
{ print("Unable to write problem in plain text format");
exit(EXIT_FAILURE);
}
}
/* write problem in GNU LP format (if required) */
if (out_glp != NULL)
{ ret = lpx_write_prob(lp, out_glp);
if (ret != 0)
{ print("Unable to write problem in GNU LP format");
exit(EXIT_FAILURE);
}
}
/* if only data check is required, skip computations */
if (check) goto skip;
/* scale the problem data (if required) */
if (scale && (!presol || method == 1)) lpx_scale_prob(lp);
/* build initial LP basis */
if (method == 0 && !presol && in_bas == NULL)
{ switch (basis)
{ case 0:
lpx_std_basis(lp);
break;
case 1:
if (lpx_get_num_rows(lp) > 0 && lpx_get_num_cols(lp) > 0)
lpx_adv_basis(lp);
break;
case 2:
if (lpx_get_num_rows(lp) > 0 && lpx_get_num_cols(lp) > 0)
lpx_cpx_basis(lp);
break;
default:
xassert(basis != basis);
}
}
/* or read initial basis from input text file in MPS format */
if (in_bas != NULL)
{ if (method != 0)
{ print("Initial LP basis is useless for interior-point solve"
"r and therefore ignored");
goto nobs;
}
lpx_set_int_parm(lp, LPX_K_MPSORIG, orig);
ret = lpx_read_bas(lp, in_bas);
if (ret != 0)
{ print("Unable to read initial LP basis");
exit(EXIT_FAILURE);
}
if (presol)
{ presol = 0;
print("LP presolver disabled because initial LP basis has b"
"een provided");
}
nobs: ;
}
/* set some control parameters, which might be changed in the
command line */
lpx_set_int_parm(lp, LPX_K_BFTYPE, bf_type);
lpx_set_int_parm(lp, LPX_K_PRICE, price);
if (!relax) lpx_set_real_parm(lp, LPX_K_RELAX, 0.0);
lpx_set_int_parm(lp, LPX_K_PRESOL, presol);
lpx_set_int_parm(lp, LPX_K_BRANCH, branch);
lpx_set_int_parm(lp, LPX_K_BTRACK, btrack);
lpx_set_real_parm(lp, LPX_K_TMLIM, (double)tmlim);
lpx_set_int_parm(lp, LPX_K_BINARIZE, binarize);
lpx_set_int_parm(lp, LPX_K_USECUTS, use_cuts);
/* solve the problem */
start = xtime();
switch (method)
{ case 0:
if (nomip || lpx_get_class(lp) == LPX_LP)
{ ret = (!exact ? lpx_simplex(lp) : lpx_exact(lp));
if (xcheck)
{ if (!presol || ret == LPX_E_OK)
lpx_exact(lp);
else
print("If you need checking final basis for non-op"
"timal solution, use --nopresol");
}
if (presol && ret != LPX_E_OK && (out_bas != NULL ||
out_sol != NULL))
print("If you need actual output for non-optimal solu"
"tion, use --nopresol");
}
else
{ method = 2;
if (!intopt)
{ ret = (!exact ? lpx_simplex(lp) : lpx_exact(lp));
if (xcheck && (!presol || ret == LPX_E_OK))
lpx_exact(lp);
lpx_integer(lp);
}
else
lpx_intopt(lp);
}
break;
case 1:
if (nomip || lpx_get_class(lp) == LPX_LP)
lpx_interior(lp);
else
{ print("Interior-point method is not able to solve MIP pr"
"oblem; use --simplex");
exit(EXIT_FAILURE);
}
break;
default:
xassert(method != method);
}
/* display statistics */
print("Time used: %.1f secs", xdifftime(xtime(), start));
{ ulong_t tpeak;
char buf[50];
lib_mem_usage(NULL, NULL, NULL, &tpeak);
print("Memory used: %.1f Mb (%s bytes)",
(4294967296.0 * tpeak.hi + tpeak.lo) / 1048576.0,
ultoa(tpeak, buf, 10));
}
if (mpl != NULL && mpl_has_solve_stmt(mpl))
{ int n, j, round;
/* store the solution to the translator database */
n = lpx_get_num_cols(lp);
round = lpx_get_int_parm(lp, LPX_K_ROUND);
lpx_set_int_parm(lp, LPX_K_ROUND, 1);
switch (method)
{ case 0:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_get_col_prim(lp, j));
break;
case 1:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_ipt_col_prim(lp, j));
break;
case 2:
for (j = 1; j <= n; j++)
mpl_put_col_value(mpl, j, lpx_mip_col_val(lp, j));
break;
default:
xassert(method != method);
}
lpx_set_int_parm(lp, LPX_K_ROUND, round);
/* perform postsolving */
ret = mpl_postsolve(mpl);
if (ret == 4)
{ print("Model postsolving error");
exit(EXIT_FAILURE);
}
xassert(ret == 3);
}
/* write final LP basis (if required) */
if (out_bas != NULL)
{ lpx_set_int_parm(lp, LPX_K_MPSORIG, orig);
ret = lpx_write_bas(lp, out_bas);
if (ret != 0)
{ print("Unable to write final LP basis");
exit(EXIT_FAILURE);
}
}
/* write problem solution found by the solver (if required) */
if (out_sol != NULL)
{ switch (method)
{ case 0:
ret = lpx_print_sol(lp, out_sol);
break;
case 1:
ret = lpx_print_ips(lp, out_sol);
break;
case 2:
ret = lpx_print_mip(lp, out_sol);
break;
default:
xassert(method != method);
}
if (ret != 0)
{ print("Unable to write problem solution");
exit(EXIT_FAILURE);
}
}
/* write sensitivity bounds information (if required) */
if (out_bnds != NULL)
{ if (method != 0)
{ print("Cannot write sensitivity bounds information for inte"
"rior-point or MIP solution");
exit(EXIT_FAILURE);
}
ret = lpx_print_sens_bnds(lp, out_bnds);
if (ret != 0)
{ print("Unable to write sensitivity bounds information");
exit(EXIT_FAILURE);
}
}
skip: /* delete the problem object */
lpx_delete_prob(lp);
/* if the translator database exists, destroy it */
if (mpl != NULL) mpl_terminate(mpl);
xassert(gmp_pool_count() == 0);
gmp_free_mem();
/* close the hardcopy file */
if (log_file != NULL) lib_close_log();
/* check that no memory blocks are still allocated */
{ int count;
ulong_t total;
lib_mem_usage(&count, NULL, &total, NULL);
xassert(count == 0);
xassert(total.lo == 0 && total.hi == 0);
}
/* free the library environment */
lib_free_env();
/* return to the control program */
return 0;
}
int CClp_limited_dualopt(CClp *lp, int iterationlim, int *status,
double *objupperlim)
{ /* CALLS the dual simplex method with a limit on the number of
pivots.
- upperbound it is used to cutoff the dual simplex method (when
the objective value reaches upperbound); it can be NULL;
- status returns the status of the optimization (it can be
NULL). */
int stat, ret;
insist(iterationlim == iterationlim);
insist(objupperlim == objupperlim);
if (MSGLEV >= 1)
{ int m = lpx_get_num_rows(lp->lp);
int n = lpx_get_num_cols(lp->lp);
int nz = lpx_get_num_nz(lp->lp);
print("CClp_limited_dualopt: m = %d; n = %d; nz = %d", m, n,
nz);
}
lpx_set_int_parm(lp->lp, LPX_K_DUAL, 1);
switch (MSGLEV)
{ case 0:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 0);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 1000000);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 1e6);
break;
case 1:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 2);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 200);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 5.0);
break;
case 2:
lpx_set_int_parm(lp->lp, LPX_K_MSGLEV, 3);
lpx_set_int_parm(lp->lp, LPX_K_OUTFRQ, 200);
lpx_set_real_parm(lp->lp, LPX_K_OUTDLY, 0.0);
break;
default:
insist(MSGLEV != MSGLEV);
}
ret = lpx_simplex(lp->lp);
if (ret == LPX_E_FAULT)
{ if (MSGLEV >= 1) print("CClp_limited_dualopt: restarting from "
"advanced basis...");
lpx_adv_basis(lp->lp);
ret = lpx_simplex(lp->lp);
}
if (ret != LPX_E_OK)
{ print("CClp_limited_dualopt: lpx_simplex failed; return code ="
" %d", ret);
if (status) *status = CClp_FAILURE;
ret = 1;
goto done;
}
stat = lpx_get_status(lp->lp);
if (stat == LPX_OPT)
{ if (status) *status = CClp_SUCCESS;
ret = 0;
}
else if (stat == LPX_NOFEAS)
{ if (status) *status = CClp_INFEASIBLE;
ret = 0;
}
else
{ print("CClp_limited_dualopt: optimization status = %d", stat);
if (status) *status = CClp_FAILURE;
ret = 1;
}
done: return ret;
}
int lpx_integer(LPX *mip)
{ int m = lpx_get_num_rows(mip);
int n = lpx_get_num_cols(mip);
MIPTREE *tree;
LPX *lp;
int ret, i, j, stat, type, len, *ind;
double lb, ub, coef, *val;
#if 0
/* the problem must be of MIP class */
if (lpx_get_class(mip) != LPX_MIP)
{ print("lpx_integer: problem is not of MIP class");
ret = LPX_E_FAULT;
goto done;
}
#endif
/* an optimal solution of LP relaxation must be known */
if (lpx_get_status(mip) != LPX_OPT)
{ print("lpx_integer: optimal solution of LP relaxation required"
);
ret = LPX_E_FAULT;
goto done;
}
/* bounds of all integer variables must be integral */
for (j = 1; j <= n; j++)
{ if (lpx_get_col_kind(mip, j) != LPX_IV) continue;
type = lpx_get_col_type(mip, j);
if (type == LPX_LO || type == LPX_DB || type == LPX_FX)
{ lb = lpx_get_col_lb(mip, j);
if (lb != floor(lb))
{ print("lpx_integer: integer column %d has non-integer lo"
"wer bound or fixed value %g", j, lb);
ret = LPX_E_FAULT;
goto done;
}
}
if (type == LPX_UP || type == LPX_DB)
{ ub = lpx_get_col_ub(mip, j);
if (ub != floor(ub))
{ print("lpx_integer: integer column %d has non-integer up"
"per bound %g", j, ub);
ret = LPX_E_FAULT;
goto done;
}
}
}
/* it seems all is ok */
if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 2)
print("Integer optimization begins...");
/* create the branch-and-bound tree */
tree = mip_create_tree(m, n, lpx_get_obj_dir(mip));
/* set up column kinds */
for (j = 1; j <= n; j++)
tree->int_col[j] = (lpx_get_col_kind(mip, j) == LPX_IV);
/* access the LP relaxation template */
lp = tree->lp;
/* set up the objective function */
tree->int_obj = 1;
for (j = 0; j <= tree->n; j++)
{ coef = lpx_get_obj_coef(mip, j);
lpx_set_obj_coef(lp, j, coef);
if (coef != 0.0 && !(tree->int_col[j] && coef == floor(coef)))
tree->int_obj = 0;
}
if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 2 && tree->int_obj)
print("Objective function is integral");
/* set up the constraint matrix */
ind = xcalloc(1+n, sizeof(int));
val = xcalloc(1+n, sizeof(double));
for (i = 1; i <= m; i++)
{ len = lpx_get_mat_row(mip, i, ind, val);
lpx_set_mat_row(lp, i, len, ind, val);
}
xfree(ind);
xfree(val);
/* set up scaling matrices */
for (i = 1; i <= m; i++)
lpx_set_rii(lp, i, lpx_get_rii(mip, i));
for (j = 1; j <= n; j++)
lpx_set_sjj(lp, j, lpx_get_sjj(mip, j));
/* revive the root subproblem */
mip_revive_node(tree, 1);
/* set up row attributes for the root subproblem */
for (i = 1; i <= m; i++)
{ type = lpx_get_row_type(mip, i);
lb = lpx_get_row_lb(mip, i);
ub = lpx_get_row_ub(mip, i);
stat = lpx_get_row_stat(mip, i);
lpx_set_row_bnds(lp, i, type, lb, ub);
lpx_set_row_stat(lp, i, stat);
}
/* set up column attributes for the root subproblem */
for (j = 1; j <= n; j++)
{ type = lpx_get_col_type(mip, j);
lb = lpx_get_col_lb(mip, j);
ub = lpx_get_col_ub(mip, j);
stat = lpx_get_col_stat(mip, j);
lpx_set_col_bnds(lp, j, type, lb, ub);
lpx_set_col_stat(lp, j, stat);
}
/* freeze the root subproblem */
mip_freeze_node(tree);
/* inherit some control parameters and statistics */
tree->msg_lev = lpx_get_int_parm(mip, LPX_K_MSGLEV);
if (tree->msg_lev > 2) tree->msg_lev = 2;
tree->branch = lpx_get_int_parm(mip, LPX_K_BRANCH);
tree->btrack = lpx_get_int_parm(mip, LPX_K_BTRACK);
tree->tol_int = lpx_get_real_parm(mip, LPX_K_TOLINT);
tree->tol_obj = lpx_get_real_parm(mip, LPX_K_TOLOBJ);
tree->tm_lim = lpx_get_real_parm(mip, LPX_K_TMLIM);
lpx_set_int_parm(lp, LPX_K_BFTYPE, lpx_get_int_parm(mip,
LPX_K_BFTYPE));
lpx_set_int_parm(lp, LPX_K_PRICE, lpx_get_int_parm(mip,
LPX_K_PRICE));
lpx_set_real_parm(lp, LPX_K_RELAX, lpx_get_real_parm(mip,
LPX_K_RELAX));
lpx_set_real_parm(lp, LPX_K_TOLBND, lpx_get_real_parm(mip,
LPX_K_TOLBND));
lpx_set_real_parm(lp, LPX_K_TOLDJ, lpx_get_real_parm(mip,
LPX_K_TOLDJ));
lpx_set_real_parm(lp, LPX_K_TOLPIV, lpx_get_real_parm(mip,
LPX_K_TOLPIV));
lpx_set_int_parm(lp, LPX_K_ITLIM, lpx_get_int_parm(mip,
LPX_K_ITLIM));
lpx_set_int_parm(lp, LPX_K_ITCNT, lpx_get_int_parm(mip,
LPX_K_ITCNT));
/* reset the status of MIP solution */
lpx_put_mip_soln(mip, LPX_I_UNDEF, NULL, NULL);
/* try solving the problem */
ret = mip_driver(tree);
/* if an integer feasible solution has been found, copy it to the
MIP problem object */
if (tree->found)
lpx_put_mip_soln(mip, LPX_I_FEAS, &tree->mipx[0],
&tree->mipx[m]);
/* copy back statistics about spent resources */
lpx_set_real_parm(mip, LPX_K_TMLIM, tree->tm_lim);
lpx_set_int_parm(mip, LPX_K_ITLIM, lpx_get_int_parm(lp,
LPX_K_ITLIM));
lpx_set_int_parm(mip, LPX_K_ITCNT, lpx_get_int_parm(lp,
LPX_K_ITCNT));
/* analyze exit code reported by the mip driver */
switch (ret)
{ case MIP_E_OK:
if (tree->found)
{ if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 3)
print("INTEGER OPTIMAL SOLUTION FOUND");
lpx_put_mip_soln(mip, LPX_I_OPT, NULL, NULL);
}
else
{ if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 3)
print("PROBLEM HAS NO INTEGER FEASIBLE SOLUTION");
lpx_put_mip_soln(mip, LPX_I_NOFEAS, NULL, NULL);
}
ret = LPX_E_OK;
break;
case MIP_E_ITLIM:
if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 3)
print("ITERATIONS LIMIT EXCEEDED; SEARCH TERMINATED");
ret = LPX_E_ITLIM;
break;
case MIP_E_TMLIM:
if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 3)
print("TIME LIMIT EXCEEDED; SEARCH TERMINATED");
ret = LPX_E_TMLIM;
break;
case MIP_E_ERROR:
if (lpx_get_int_parm(mip, LPX_K_MSGLEV) >= 1)
print("lpx_integer: cannot solve current LP relaxation");
ret = LPX_E_SING;
break;
default:
xassert(ret != ret);
}
/* delete the branch-and-bound tree */
mip_delete_tree(tree);
done: /* return to the application program */
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();
// Obsolete
//lib_set_fault_hook (NULL, glpk_fault_hook);
//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
glp_prob *lp = glp_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])
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;
}
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 (lpx_write_cpxlp (lp, save_filename) != 0) {
mexErrMsgTxt("glpkcc: unable to write the problem");
longjmp (mark, -1);
}
}else{
if (!strcmp(filetype,"fixedmps")){
if (lpx_write_mps (lp, save_filename) != 0) {
mexErrMsgTxt("glpkcc: unable to write the problem");
longjmp (mark, -1);
}
}else{
if (!strcmp(filetype,"freemps")){
if (lpx_write_freemps (lp, save_filename) != 0) {
mexErrMsgTxt("glpkcc: unable to write the problem");
longjmp (mark, -1);
}
}else{// plain text
if (lpx_print_prob (lp, save_filename) != 0) {
mexErrMsgTxt("glpkcc: unable to write the problem");
longjmp (mark, -1);
}
}
}
}
}
//-- scale the problem data (if required)
if (glpIntParam[1] && (! glpIntParam[16] || lpsolver != 1))
lpx_scale_prob (lp);
//-- build advanced initial basis (if required)
if (lpsolver == 1 && ! glpIntParam[16])
lpx_adv_basis (lp);
glp_smcp sParam;
glp_init_smcp(&sParam);
//-- set control parameters
if (lpsolver==1){
//remap of control parameters for simplex method
sParam.msg_lev=glpIntParam[0]; // message level
// simplex method: primal/dual
if (glpIntParam[2]==0) sParam.meth=GLP_PRIMAL;
else sParam.meth=GLP_DUALP;
// pricing technique
if (glpIntParam[3]==0) sParam.pricing=GLP_PT_STD;
else sParam.pricing=GLP_PT_PSE;
//sParam.r_test not available
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++)
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]);
}
// Choose simplex method ('S') or interior point method ('T') to solve the problem
if (lpsolver == 1)
method = 'S';
else
method = 'T';
int errnum;
switch (method){
case 'S': {
if (isMIP){
method = 'I';
errnum = lpx_intopt (lp);
}
else{
errnum = glp_simplex(lp, &sParam);
errnum += 100; //this is to avoid ambiguity in the return codes.
}
}
break;
case 'T': errnum = lpx_interior(lp); break;
default: xassert (method != method);
}
/* errnum assumes the following results:
errnum = 0 <=> No errors
errnum = 1 <=> Iteration limit exceeded.
errnum = 2 <=> Numerical problems with basis matrix.
*/
if (errnum == LPX_E_OK || errnum==100){
// Get status and object value
if (isMIP)
{
*status = glp_mip_status (lp);
*fmin = glp_mip_obj_val (lp);
}
else
{
if (lpsolver == 1)
{
*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)
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) 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) 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;
glp_ulong tpeak;
lib_mem_usage(NULL, NULL, NULL, &tpeak);
*mem=(double)(4294967296.0 * tpeak.hi + tpeak.lo) / (1024);
glp_delete_prob (lp);
return 0;
}
glp_delete_prob (lp);
*status = errnum;
return errnum;
}
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;
}
static int Params_parameter_set(ParamsObject *self, PyObject *value,
struct param_getsets *pgs) {
if (value == NULL) {
// Maybe in future this should restore to default, but I can't be arsed.
PyErr_Format(PyExc_TypeError,"cannot delete attribute '%s'",
pgs->attr_name);
return -1;
}
switch (pgs->type) {
case 0: { // Boolean.
int truth = PyObject_IsTrue(value);
if (truth < 0) return -1;
lpx_set_int_parm(LP, pgs->code, truth);
return 0;
}
case 1: { // Integer.
if (!PyInt_Check(value)) {
PyErr_Format(PyExc_TypeError, "attribute '%s' requires an int",
pgs->attr_name);
return -1;
}
int val = PyInt_AS_LONG(value);
// Do all that range checking.
if (pgs->low < pgs->high) {
if (pgs->low > val) {
PyErr_Format(PyExc_ValueError,"attribute '%s' must be at least %d",
pgs->attr_name, (int)pgs->low);
return -1;
}
if (pgs->high < val) {
PyErr_Format(PyExc_ValueError,"attribute '%s' must be at most %d",
pgs->attr_name, (int)pgs->high);
return -1;
}
}
// It's in range. Set it.
lpx_set_int_parm(LP, pgs->code, val);
return 0;
}
case 2: { // Float.
value = PyNumber_Float(value);
if (value == NULL) {
PyErr_Format(PyExc_TypeError, "attribute %s requires a float",
pgs->attr_name);
return -1;
}
double val = PyFloat_AS_DOUBLE(value);
Py_DECREF(value);
// Do the range checking.
if (pgs->low < pgs->high) {
if ((!pgs->include_low && pgs->low==val) || pgs->low>val) {
char buffer[100];
snprintf(buffer, sizeof(buffer), "attribute '%s' must be %s %g",
pgs->attr_name, pgs->include_low?"at least":"greater than",
pgs->low);
PyErr_SetString(PyExc_ValueError, buffer);
return -1;
}
if ((!pgs->include_high && pgs->high==val) || pgs->high<val) {
char buffer[100];
snprintf(buffer, sizeof(buffer), "attribute '%s' must be %s %g",
pgs->attr_name, pgs->include_high?"at most":"less than",
pgs->high);
PyErr_SetString(PyExc_ValueError, buffer);
return -1;
}
}
// It's in range. Set it.
lpx_set_real_parm(LP, pgs->code, val);
return 0;
}
default: // Um, apparently I made a mistake in the PGS definition array.
PyErr_Format(PyExc_RuntimeError, "parameter type code %d unrecognized",
pgs->type);
return -1;
}
}
int lpx_intopt(LPX *_mip)
{ IPP *ipp = NULL;
LPX *orig = _mip, *prob = NULL;
int orig_m, orig_n, i, j, ret, i_stat;
/* the problem must be of MIP class */
if (lpx_get_class(orig) != LPX_MIP)
{ print("lpx_intopt: problem is not of MIP class");
ret = LPX_E_FAULT;
goto done;
}
/* the problem must have at least one row and one column */
orig_m = lpx_get_num_rows(orig);
orig_n = lpx_get_num_cols(orig);
if (!(orig_m > 0 && orig_n > 0))
{ print("lpx_intopt: problem has no rows/columns");
ret = LPX_E_FAULT;
goto done;
}
/* check that each double-bounded row and column has bounds */
for (i = 1; i <= orig_m; i++)
{ if (lpx_get_row_type(orig, i) == LPX_DB)
{ if (lpx_get_row_lb(orig, i) >= lpx_get_row_ub(orig, i))
{ print("lpx_intopt: row %d has incorrect bounds", i);
ret = LPX_E_FAULT;
goto done;
}
}
}
for (j = 1; j <= orig_n; j++)
{ if (lpx_get_col_type(orig, j) == LPX_DB)
{ if (lpx_get_col_lb(orig, j) >= lpx_get_col_ub(orig, j))
{ print("lpx_intopt: column %d has incorrect bounds", j);
ret = LPX_E_FAULT;
goto done;
}
}
}
/* bounds of all integer variables must be integral */
for (j = 1; j <= orig_n; j++)
{ int type;
double lb, ub;
if (lpx_get_col_kind(orig, j) != LPX_IV) continue;
type = lpx_get_col_type(orig, j);
if (type == LPX_LO || type == LPX_DB || type == LPX_FX)
{ lb = lpx_get_col_lb(orig, j);
if (lb != floor(lb))
{ print("lpx_intopt: integer column %d has non-integer low"
"er bound or fixed value %g", j, lb);
ret = LPX_E_FAULT;
goto done;
}
}
if (type == LPX_UP || type == LPX_DB)
{ ub = lpx_get_col_ub(orig, j);
if (ub != floor(ub))
{ print("lpx_intopt: integer column %d has non-integer upp"
"er bound %g", j, ub);
ret = LPX_E_FAULT;
goto done;
}
}
}
/* reset the status of MIP solution */
lpx_put_mip_soln(orig, LPX_I_UNDEF, NULL, NULL);
/* create MIP presolver workspace */
ipp = ipp_create_wksp();
/* load the original problem into the presolver workspace */
ipp_load_orig(ipp, orig);
/* perform basic MIP presolve analysis */
switch (ipp_basic_tech(ipp))
{ case 0:
/* no infeasibility is detected */
break;
case 1:
nopfs: /* primal infeasibility is detected */
print("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION");
ret = LPX_E_NOPFS;
goto done;
case 2:
/* dual infeasibility is detected */
nodfs: print("LP RELAXATION HAS NO DUAL FEASIBLE SOLUTION");
ret = LPX_E_NODFS;
goto done;
default:
insist(ipp != ipp);
}
/* reduce column bounds */
switch (ipp_reduce_bnds(ipp))
{ case 0: break;
case 1: goto nopfs;
default: insist(ipp != ipp);
}
/* perform basic MIP presolve analysis */
switch (ipp_basic_tech(ipp))
{ case 0: break;
case 1: goto nopfs;
case 2: goto nodfs;
default: insist(ipp != ipp);
}
/* replace general integer variables by sum of binary variables,
if required */
if (lpx_get_int_parm(orig, LPX_K_BINARIZE))
ipp_binarize(ipp);
/* perform coefficient reduction */
ipp_reduction(ipp);
/* if the resultant problem is empty, it has an empty solution,
which is optimal */
if (ipp->row_ptr == NULL || ipp->col_ptr == NULL)
{ insist(ipp->row_ptr == NULL);
insist(ipp->col_ptr == NULL);
print("Objective value = %.10g",
ipp->orig_dir == LPX_MIN ? +ipp->c0 : -ipp->c0);
print("INTEGER OPTIMAL SOLUTION FOUND BY MIP PRESOLVER");
/* allocate recovered solution segment */
ipp->col_stat = ucalloc(1+ipp->ncols, sizeof(int));
ipp->col_mipx = ucalloc(1+ipp->ncols, sizeof(double));
for (j = 1; j <= ipp->ncols; j++) ipp->col_stat[j] = 0;
/* perform MIP postsolve processing */
ipp_postsolve(ipp);
/* unload recovered MIP solution and store it in the original
problem object */
ipp_unload_sol(ipp, orig, LPX_I_OPT);
ret = LPX_E_OK;
goto done;
}
/* build resultant MIP problem object */
prob = ipp_build_prob(ipp);
/* display some statistics */
{ int m = lpx_get_num_rows(prob);
int n = lpx_get_num_cols(prob);
int nnz = lpx_get_num_nz(prob);
int ni = lpx_get_num_int(prob);
int nb = lpx_get_num_bin(prob);
char s[50];
print("lpx_intopt: presolved MIP has %d row%s, %d column%s, %d"
" non-zero%s", m, m == 1 ? "" : "s", n, n == 1 ? "" : "s",
nnz, 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);
print("lpx_intopt: %d integer column%s, %s which %s binary",
ni, ni == 1 ? "" : "s", s, nb == 1 ? "is" : "are");
}
/* inherit some control parameters and statistics */
lpx_set_int_parm(prob, LPX_K_PRICE, lpx_get_int_parm(orig,
LPX_K_PRICE));
lpx_set_real_parm(prob, LPX_K_RELAX, lpx_get_real_parm(orig,
LPX_K_RELAX));
lpx_set_real_parm(prob, LPX_K_TOLBND, lpx_get_real_parm(orig,
LPX_K_TOLBND));
lpx_set_real_parm(prob, LPX_K_TOLDJ, lpx_get_real_parm(orig,
LPX_K_TOLDJ));
lpx_set_real_parm(prob, LPX_K_TOLPIV, lpx_get_real_parm(orig,
LPX_K_TOLPIV));
lpx_set_int_parm(prob, LPX_K_ITLIM, lpx_get_int_parm(orig,
LPX_K_ITLIM));
lpx_set_int_parm(prob, LPX_K_ITCNT, lpx_get_int_parm(orig,
LPX_K_ITCNT));
lpx_set_real_parm(prob, LPX_K_TMLIM, lpx_get_real_parm(orig,
LPX_K_TMLIM));
lpx_set_int_parm(prob, LPX_K_BRANCH, lpx_get_int_parm(orig,
LPX_K_BRANCH));
lpx_set_int_parm(prob, LPX_K_BTRACK, lpx_get_int_parm(orig,
LPX_K_BTRACK));
lpx_set_real_parm(prob, LPX_K_TOLINT, lpx_get_real_parm(orig,
LPX_K_TOLINT));
lpx_set_real_parm(prob, LPX_K_TOLOBJ, lpx_get_real_parm(orig,
LPX_K_TOLOBJ));
/* build an advanced initial basis */
lpx_adv_basis(prob);
/* solve LP relaxation */
print("Solving LP relaxation...");
switch (lpx_simplex(prob))
{ case LPX_E_OK:
break;
case LPX_E_ITLIM:
ret = LPX_E_ITLIM;
goto done;
case LPX_E_TMLIM:
ret = LPX_E_TMLIM;
goto done;
default:
print("lpx_intopt: cannot solve LP relaxation");
ret = LPX_E_SING;
goto done;
}
/* analyze status of the basic solution */
switch (lpx_get_status(prob))
{ case LPX_OPT:
break;
case LPX_NOFEAS:
ret = LPX_E_NOPFS;
goto done;
case LPX_UNBND:
ret = LPX_E_NODFS;
goto done;
default:
insist(prob != prob);
}
/* generate cutting planes, if necessary */
if (lpx_get_int_parm(orig, LPX_K_USECUTS))
{ ret = generate_cuts(prob);
if (ret != LPX_E_OK) goto done;
}
/* call the branch-and-bound solver */
ret = lpx_integer(prob);
/* determine status of MIP solution */
i_stat = lpx_mip_status(prob);
if (i_stat == LPX_I_OPT || i_stat == LPX_I_FEAS)
{ /* load MIP solution of the resultant problem into presolver
workspace */
ipp_load_sol(ipp, prob);
/* perform MIP postsolve processing */
ipp_postsolve(ipp);
/* unload recovered MIP solution and store it in the original
problem object */
ipp_unload_sol(ipp, orig, i_stat);
}
else
{ /* just set the status of MIP solution */
lpx_put_mip_soln(orig, i_stat, NULL, NULL);
}
done: /* copy back statistics about spent resources */
if (prob != NULL)
{ lpx_set_int_parm(orig, LPX_K_ITLIM, lpx_get_int_parm(prob,
LPX_K_ITLIM));
lpx_set_int_parm(orig, LPX_K_ITCNT, lpx_get_int_parm(prob,
LPX_K_ITCNT));
lpx_set_real_parm(orig, LPX_K_TMLIM, lpx_get_real_parm(prob,
LPX_K_TMLIM));
}
/* delete the resultant problem object */
if (prob != NULL) lpx_delete_prob(prob);
/* delete MIP presolver workspace */
if (ipp != NULL) ipp_delete_wksp(ipp);
return ret;
}
static int generate_cuts(LPX *prob)
{ int prob_m, prob_n, prob_nz, msg_lev, dual, nrows, it_cnt, ret;
double out_dly, tm_lim, tm_lag = 0.0, tm_beg = utime();
print("Generating cutting planes...");
/* determine the number of rows, columns, and non-zeros on entry
to the routine */
prob_m = lpx_get_num_rows(prob);
prob_n = lpx_get_num_cols(prob);
prob_nz = lpx_get_num_nz(prob);
/* save some control parameters */
msg_lev = lpx_get_int_parm(prob, LPX_K_MSGLEV);
dual = lpx_get_int_parm(prob, LPX_K_DUAL);
out_dly = lpx_get_real_parm(prob, LPX_K_OUTDLY);
tm_lim = lpx_get_real_parm(prob, LPX_K_TMLIM);
/* and set their new values needed for re-optimization */
lpx_set_int_parm(prob, LPX_K_MSGLEV, 1);
lpx_set_int_parm(prob, LPX_K_DUAL, 1);
lpx_set_real_parm(prob, LPX_K_OUTDLY, 10.0);
lpx_set_real_parm(prob, LPX_K_TMLIM, -1.0);
loop: /* main loop starts here */
/* display current status of the problem */
if (utime() - tm_lag >= 5.0 - 0.001)
show_status(prob, prob_m, prob_nz), tm_lag = utime();
/* check if the patience has been exhausted */
if (tm_lim >= 0.0 && tm_lim <= utime() - tm_beg)
{ ret = LPX_E_TMLIM;
goto done;
}
/* not more than 500 cut inequalities are allowed */
if (lpx_get_num_rows(prob) - prob_m >= 500)
{ ret = LPX_E_OK;
goto done;
}
/* not more than 50,000 cut coefficients are allowed */
if (lpx_get_num_nz(prob) - prob_nz >= 50000)
{ ret = LPX_E_OK;
goto done;
}
/* try to generate Gomory's mixed integer cut */
nrows = lpx_get_num_rows(prob);
gen_gomory_cut(prob, prob_n);
if (nrows == lpx_get_num_rows(prob))
{ /* nothing has been generated */
ret = LPX_E_OK;
goto done;
}
/* re-optimize current LP relaxation using dual simplex */
it_cnt = lpx_get_int_parm(prob, LPX_K_ITCNT);
switch (lpx_simplex(prob))
{ case LPX_E_OK:
break;
case LPX_E_ITLIM:
ret = LPX_E_ITLIM;
goto done;
default:
ret = LPX_E_SING;
goto done;
}
if (it_cnt == lpx_get_int_parm(prob, LPX_K_ITCNT))
{ ret = LPX_E_OK;
goto done;
}
/* analyze status of the basic solution */
switch (lpx_get_status(prob))
{ case LPX_OPT:
break;
case LPX_NOFEAS:
ret = LPX_E_NOPFS;
goto done;
default:
insist(prob != prob);
}
/* continue generating cutting planes */
goto loop;
done: /* display final status of the problem */
show_status(prob, prob_m, prob_nz);
switch (ret)
{ case LPX_E_OK:
break;
case LPX_E_NOPFS:
print("PROBLEM HAS NO INTEGER FEASIBLE SOLUTION");
break;
case LPX_E_ITLIM:
print("ITERATIONS LIMIT EXCEEDED; SEARCH TERMINATED");
break;
case LPX_E_TMLIM:
print("TIME LIMIT EXCEEDED; SEARCH TERMINATED");
break;
case LPX_E_SING:
print("lpx_intopt: cannot re-optimize LP relaxation");
break;
default:
insist(ret != ret);
}
/* decrease the time limit by spent amount of the time */
if (tm_lim >= 0.0)
{ tm_lim -= (utime() - tm_beg);
if (tm_lim < 0.0) tm_lim = 0.0;
}
/* restore some control parameters and update statistics */
lpx_set_int_parm(prob, LPX_K_MSGLEV, msg_lev);
lpx_set_int_parm(prob, LPX_K_DUAL, dual);
lpx_set_real_parm(prob, LPX_K_OUTDLY, out_dly);
lpx_set_real_parm(prob, LPX_K_TMLIM, tm_lim);
return ret;
}
