static void parse_objective(struct csa *csa)
{ /* parse objective sense */
int k, len;
/* parse the keyword 'minimize' or 'maximize' */
if (csa->token == T_MINIMIZE)
glp_set_obj_dir(csa->P, GLP_MIN);
else if (csa->token == T_MAXIMIZE)
glp_set_obj_dir(csa->P, GLP_MAX);
else
xassert(csa != csa);
scan_token(csa);
/* parse objective name */
if (csa->token == T_NAME && csa->c == ':')
{ /* objective name is followed by a colon */
glp_set_obj_name(csa->P, csa->image);
scan_token(csa);
xassert(csa->token == T_COLON);
scan_token(csa);
}
else
{ /* objective name is not specified; use default */
glp_set_obj_name(csa->P, "obj");
}
/* parse linear form */
len = parse_linear_form(csa);
for (k = 1; k <= len; k++)
glp_set_obj_coef(csa->P, csa->ind[k], csa->val[k]);
return;
}
void glp_copy_prob(glp_prob *dest, glp_prob *prob, int names)
{ glp_tree *tree = dest->tree;
glp_bfcp bfcp;
int i, j, len, *ind;
double *val;
if (tree != NULL && tree->reason != 0)
xerror("glp_copy_prob: operation not allowed\n");
if (dest == prob)
xerror("glp_copy_prob: copying problem object to itself not al"
"lowed\n");
if (!(names == GLP_ON || names == GLP_OFF))
xerror("glp_copy_prob: names = %d; invalid parameter\n",
names);
glp_erase_prob(dest);
if (names && prob->name != NULL)
glp_set_prob_name(dest, prob->name);
if (names && prob->obj != NULL)
glp_set_obj_name(dest, prob->obj);
dest->dir = prob->dir;
dest->c0 = prob->c0;
if (prob->m > 0)
glp_add_rows(dest, prob->m);
if (prob->n > 0)
glp_add_cols(dest, prob->n);
glp_get_bfcp(prob, &bfcp);
glp_set_bfcp(dest, &bfcp);
dest->pbs_stat = prob->pbs_stat;
dest->dbs_stat = prob->dbs_stat;
dest->obj_val = prob->obj_val;
dest->some = prob->some;
dest->ipt_stat = prob->ipt_stat;
dest->ipt_obj = prob->ipt_obj;
dest->mip_stat = prob->mip_stat;
dest->mip_obj = prob->mip_obj;
for (i = 1; i <= prob->m; i++)
{ GLPROW *to = dest->row[i];
GLPROW *from = prob->row[i];
if (names && from->name != NULL)
glp_set_row_name(dest, i, from->name);
to->type = from->type;
to->lb = from->lb;
to->ub = from->ub;
to->rii = from->rii;
to->stat = from->stat;
to->prim = from->prim;
to->dual = from->dual;
to->pval = from->pval;
to->dval = from->dval;
to->mipx = from->mipx;
}
ind = xcalloc(1+prob->m, sizeof(int));
val = xcalloc(1+prob->m, sizeof(double));
for (j = 1; j <= prob->n; j++)
{ GLPCOL *to = dest->col[j];
GLPCOL *from = prob->col[j];
if (names && from->name != NULL)
glp_set_col_name(dest, j, from->name);
to->kind = from->kind;
to->type = from->type;
to->lb = from->lb;
to->ub = from->ub;
to->coef = from->coef;
len = glp_get_mat_col(prob, j, ind, val);
glp_set_mat_col(dest, j, len, ind, val);
to->sjj = from->sjj;
to->stat = from->stat;
to->prim = from->prim;
to->dual = from->dual;
to->pval = from->pval;
to->dval = from->dval;
to->mipx = from->mipx;
}
xfree(ind);
xfree(val);
return;
}
void npp_build_prob(NPP *npp, glp_prob *prob)
{ /* build resultant (preprocessed) problem */
NPPROW *row;
NPPCOL *col;
NPPAIJ *aij;
int i, j, type, len, *ind;
double dir, *val;
glp_erase_prob(prob);
glp_set_prob_name(prob, npp->name);
glp_set_obj_name(prob, npp->obj);
glp_set_obj_dir(prob, npp->orig_dir);
if (npp->orig_dir == GLP_MIN)
dir = +1.0;
else if (npp->orig_dir == GLP_MAX)
dir = -1.0;
else
xassert(npp != npp);
glp_set_obj_coef(prob, 0, dir * npp->c0);
/* build rows */
for (row = npp->r_head; row != NULL; row = row->next)
{ row->temp = i = glp_add_rows(prob, 1);
glp_set_row_name(prob, i, row->name);
if (row->lb == -DBL_MAX && row->ub == +DBL_MAX)
type = GLP_FR;
else if (row->ub == +DBL_MAX)
type = GLP_LO;
else if (row->lb == -DBL_MAX)
type = GLP_UP;
else if (row->lb != row->ub)
type = GLP_DB;
else
type = GLP_FX;
glp_set_row_bnds(prob, i, type, row->lb, row->ub);
}
/* build columns and the constraint matrix */
ind = xcalloc(1+prob->m, sizeof(int));
val = xcalloc(1+prob->m, sizeof(double));
for (col = npp->c_head; col != NULL; col = col->next)
{ j = glp_add_cols(prob, 1);
glp_set_col_name(prob, j, col->name);
#if 0
glp_set_col_kind(prob, j, col->kind);
#else
glp_set_col_kind(prob, j, col->is_int ? GLP_IV : GLP_CV);
#endif
if (col->lb == -DBL_MAX && col->ub == +DBL_MAX)
type = GLP_FR;
else if (col->ub == +DBL_MAX)
type = GLP_LO;
else if (col->lb == -DBL_MAX)
type = GLP_UP;
else if (col->lb != col->ub)
type = GLP_DB;
else
type = GLP_FX;
glp_set_col_bnds(prob, j, type, col->lb, col->ub);
glp_set_obj_coef(prob, j, dir * col->coef);
len = 0;
for (aij = col->ptr; aij != NULL; aij = aij->c_next)
{ len++;
ind[len] = aij->row->temp;
val[len] = aij->val;
}
glp_set_mat_col(prob, j, len, ind, val);
}
xfree(ind);
xfree(val);
/* resultant problem has been built */
npp->m = prob->m;
npp->n = prob->n;
npp->nnz = prob->nnz;
npp->row_ref = xcalloc(1+npp->m, sizeof(int));
npp->col_ref = xcalloc(1+npp->n, sizeof(int));
for (row = npp->r_head, i = 0; row != NULL; row = row->next)
npp->row_ref[++i] = row->i;
for (col = npp->c_head, j = 0; col != NULL; col = col->next)
npp->col_ref[++j] = col->j;
/* transformed problem segment is no longer needed */
dmp_delete_pool(npp->pool), npp->pool = NULL;
npp->name = npp->obj = NULL;
npp->c0 = 0.0;
npp->r_head = npp->r_tail = NULL;
npp->c_head = npp->c_tail = NULL;
return;
}
void glp_mpl_build_prob(glp_tran *tran, glp_prob *prob)
{ /* build LP/MIP problem instance from the model */
int m, n, i, j, t, kind, type, len, *ind;
double lb, ub, *val;
if (tran->phase != 3)
xerror("glp_mpl_build_prob: invalid call sequence\n");
/* erase the problem object */
glp_erase_prob(prob);
/* set problem name */
glp_set_prob_name(prob, mpl_get_prob_name(tran));
/* build rows (constraints) */
m = mpl_get_num_rows(tran);
if (m > 0)
glp_add_rows(prob, m);
for (i = 1; i <= m; i++)
{ /* set row name */
glp_set_row_name(prob, i, mpl_get_row_name(tran, i));
/* set row bounds */
type = mpl_get_row_bnds(tran, i, &lb, &ub);
switch (type)
{ case MPL_FR: type = GLP_FR; break;
case MPL_LO: type = GLP_LO; break;
case MPL_UP: type = GLP_UP; break;
case MPL_DB: type = GLP_DB; break;
case MPL_FX: type = GLP_FX; break;
default: xassert(type != type);
}
if (type == GLP_DB && fabs(lb - ub) < 1e-9 * (1.0 + fabs(lb)))
{ type = GLP_FX;
if (fabs(lb) <= fabs(ub)) ub = lb; else lb = ub;
}
glp_set_row_bnds(prob, i, type, lb, ub);
/* warn about non-zero constant term */
if (mpl_get_row_c0(tran, i) != 0.0)
xprintf("glp_mpl_build_prob: row %s; constant term %.12g ig"
"nored\n",
mpl_get_row_name(tran, i), mpl_get_row_c0(tran, i));
}
/* build columns (variables) */
n = mpl_get_num_cols(tran);
if (n > 0)
glp_add_cols(prob, n);
for (j = 1; j <= n; j++)
{ /* set column name */
glp_set_col_name(prob, j, mpl_get_col_name(tran, j));
/* set column kind */
kind = mpl_get_col_kind(tran, j);
switch (kind)
{ case MPL_NUM:
break;
case MPL_INT:
case MPL_BIN:
glp_set_col_kind(prob, j, GLP_IV);
break;
default:
xassert(kind != kind);
}
/* set column bounds */
type = mpl_get_col_bnds(tran, j, &lb, &ub);
switch (type)
{ case MPL_FR: type = GLP_FR; break;
case MPL_LO: type = GLP_LO; break;
case MPL_UP: type = GLP_UP; break;
case MPL_DB: type = GLP_DB; break;
case MPL_FX: type = GLP_FX; break;
default: xassert(type != type);
}
if (kind == MPL_BIN)
{ if (type == GLP_FR || type == GLP_UP || lb < 0.0) lb = 0.0;
if (type == GLP_FR || type == GLP_LO || ub > 1.0) ub = 1.0;
type = GLP_DB;
}
if (type == GLP_DB && fabs(lb - ub) < 1e-9 * (1.0 + fabs(lb)))
{ type = GLP_FX;
if (fabs(lb) <= fabs(ub)) ub = lb; else lb = ub;
}
glp_set_col_bnds(prob, j, type, lb, ub);
}
/* load the constraint matrix */
ind = xcalloc(1+n, sizeof(int));
val = xcalloc(1+n, sizeof(double));
for (i = 1; i <= m; i++)
{ len = mpl_get_mat_row(tran, i, ind, val);
glp_set_mat_row(prob, i, len, ind, val);
}
/* build objective function (the first objective is used) */
for (i = 1; i <= m; i++)
{ kind = mpl_get_row_kind(tran, i);
if (kind == MPL_MIN || kind == MPL_MAX)
{ /* set objective name */
glp_set_obj_name(prob, mpl_get_row_name(tran, i));
/* set optimization direction */
glp_set_obj_dir(prob, kind == MPL_MIN ? GLP_MIN : GLP_MAX);
/* set constant term */
glp_set_obj_coef(prob, 0, mpl_get_row_c0(tran, i));
/* set objective coefficients */
len = mpl_get_mat_row(tran, i, ind, val);
for (t = 1; t <= len; t++)
glp_set_obj_coef(prob, ind[t], val[t]);
break;
}
}
/* free working arrays */
xfree(ind);
xfree(val);
return;
}
void lpx_set_obj_name(LPX *lp, const char *name)
{ /* assign (change) objective function name */
glp_set_obj_name(lp, name);
return;
}
int glp_read_prob(glp_prob *P, int flags, const char *fname)
{ DMX _csa, *csa = &_csa;
int mip, m, n, nnz, ne, i, j, k, type, kind, ret, *ln = NULL,
*ia = NULL, *ja = NULL;
double lb, ub, temp, *ar = NULL;
char *rf = NULL, *cf = NULL;
if (P == NULL || P->magic != GLP_PROB_MAGIC)
xerror("glp_read_prob: P = %p; invalid problem object\n",
P);
if (flags != 0)
xerror("glp_read_prob: flags = %d; invalid parameter\n",
flags);
if (fname == NULL)
xerror("glp_read_prob: fname = %d; invalid parameter\n",
fname);
glp_erase_prob(P);
if (setjmp(csa->jump))
{ ret = 1;
goto done;
}
csa->fname = fname;
csa->fp = NULL;
csa->count = 0;
csa->c = '\n';
csa->field[0] = '\0';
csa->empty = csa->nonint = 0;
xprintf("Reading problem data from '%s'...\n", fname);
csa->fp = glp_open(fname, "r");
if (csa->fp == NULL)
{ xprintf("Unable to open '%s' - %s\n", fname, get_err_msg());
longjmp(csa->jump, 1);
}
/* read problem line */
read_designator(csa);
if (strcmp(csa->field, "p") != 0)
error(csa, "problem line missing or invalid");
read_field(csa);
if (strcmp(csa->field, "lp") == 0)
mip = 0;
else if (strcmp(csa->field, "mip") == 0)
mip = 1;
else
error(csa, "wrong problem designator; 'lp' or 'mip' expected");
read_field(csa);
if (strcmp(csa->field, "min") == 0)
glp_set_obj_dir(P, GLP_MIN);
else if (strcmp(csa->field, "max") == 0)
glp_set_obj_dir(P, GLP_MAX);
else
error(csa, "objective sense missing or invalid");
read_field(csa);
if (!(str2int(csa->field, &m) == 0 && m >= 0))
error(csa, "number of rows missing or invalid");
read_field(csa);
if (!(str2int(csa->field, &n) == 0 && n >= 0))
error(csa, "number of columns missing or invalid");
read_field(csa);
if (!(str2int(csa->field, &nnz) == 0 && nnz >= 0))
error(csa, "number of constraint coefficients missing or inval"
"id");
if (m > 0)
{ glp_add_rows(P, m);
for (i = 1; i <= m; i++)
glp_set_row_bnds(P, i, GLP_FX, 0.0, 0.0);
}
if (n > 0)
{ glp_add_cols(P, n);
for (j = 1; j <= n; j++)
{ if (!mip)
glp_set_col_bnds(P, j, GLP_LO, 0.0, 0.0);
else
glp_set_col_kind(P, j, GLP_BV);
}
}
end_of_line(csa);
/* allocate working arrays */
rf = xcalloc(1+m, sizeof(char));
memset(rf, 0, 1+m);
cf = xcalloc(1+n, sizeof(char));
memset(cf, 0, 1+n);
ln = xcalloc(1+nnz, sizeof(int));
ia = xcalloc(1+nnz, sizeof(int));
ja = xcalloc(1+nnz, sizeof(int));
ar = xcalloc(1+nnz, sizeof(double));
/* read descriptor lines */
ne = 0;
for (;;)
{ read_designator(csa);
if (strcmp(csa->field, "i") == 0)
{ /* row descriptor */
read_field(csa);
if (str2int(csa->field, &i) != 0)
error(csa, "row number missing or invalid");
if (!(1 <= i && i <= m))
error(csa, "row number out of range");
read_field(csa);
if (strcmp(csa->field, "f") == 0)
type = GLP_FR;
else if (strcmp(csa->field, "l") == 0)
type = GLP_LO;
else if (strcmp(csa->field, "u") == 0)
type = GLP_UP;
else if (strcmp(csa->field, "d") == 0)
type = GLP_DB;
else if (strcmp(csa->field, "s") == 0)
type = GLP_FX;
else
error(csa, "row type missing or invalid");
if (type == GLP_LO || type == GLP_DB || type == GLP_FX)
{ read_field(csa);
if (str2num(csa->field, &lb) != 0)
error(csa, "row lower bound/fixed value missing or in"
"valid");
}
else
lb = 0.0;
if (type == GLP_UP || type == GLP_DB)
{ read_field(csa);
if (str2num(csa->field, &ub) != 0)
error(csa, "row upper bound missing or invalid");
}
else
ub = 0.0;
if (rf[i] & 0x01)
error(csa, "duplicate row descriptor");
glp_set_row_bnds(P, i, type, lb, ub), rf[i] |= 0x01;
}
else if (strcmp(csa->field, "j") == 0)
{ /* column descriptor */
read_field(csa);
if (str2int(csa->field, &j) != 0)
error(csa, "column number missing or invalid");
if (!(1 <= j && j <= n))
error(csa, "column number out of range");
if (!mip)
kind = GLP_CV;
else
{ read_field(csa);
if (strcmp(csa->field, "c") == 0)
kind = GLP_CV;
else if (strcmp(csa->field, "i") == 0)
kind = GLP_IV;
else if (strcmp(csa->field, "b") == 0)
{ kind = GLP_IV;
type = GLP_DB, lb = 0.0, ub = 1.0;
goto skip;
}
else
error(csa, "column kind missing or invalid");
}
read_field(csa);
if (strcmp(csa->field, "f") == 0)
type = GLP_FR;
else if (strcmp(csa->field, "l") == 0)
type = GLP_LO;
else if (strcmp(csa->field, "u") == 0)
type = GLP_UP;
else if (strcmp(csa->field, "d") == 0)
type = GLP_DB;
else if (strcmp(csa->field, "s") == 0)
type = GLP_FX;
else
error(csa, "column type missing or invalid");
if (type == GLP_LO || type == GLP_DB || type == GLP_FX)
{ read_field(csa);
if (str2num(csa->field, &lb) != 0)
error(csa, "column lower bound/fixed value missing or"
" invalid");
}
else
lb = 0.0;
if (type == GLP_UP || type == GLP_DB)
{ read_field(csa);
if (str2num(csa->field, &ub) != 0)
error(csa, "column upper bound missing or invalid");
}
else
ub = 0.0;
skip: if (cf[j] & 0x01)
error(csa, "duplicate column descriptor");
glp_set_col_kind(P, j, kind);
glp_set_col_bnds(P, j, type, lb, ub), cf[j] |= 0x01;
}
else if (strcmp(csa->field, "a") == 0)
{ /* coefficient descriptor */
read_field(csa);
if (str2int(csa->field, &i) != 0)
error(csa, "row number missing or invalid");
if (!(0 <= i && i <= m))
error(csa, "row number out of range");
read_field(csa);
if (str2int(csa->field, &j) != 0)
error(csa, "column number missing or invalid");
if (!((i == 0 ? 0 : 1) <= j && j <= n))
error(csa, "column number out of range");
read_field(csa);
if (i == 0)
{ if (str2num(csa->field, &temp) != 0)
error(csa, "objective %s missing or invalid",
j == 0 ? "constant term" : "coefficient");
if (cf[j] & 0x10)
error(csa, "duplicate objective %s",
j == 0 ? "constant term" : "coefficient");
glp_set_obj_coef(P, j, temp), cf[j] |= 0x10;
}
else
{ if (str2num(csa->field, &temp) != 0)
error(csa, "constraint coefficient missing or invalid"
);
if (ne == nnz)
error(csa, "too many constraint coefficient descripto"
"rs");
ln[++ne] = csa->count;
ia[ne] = i, ja[ne] = j, ar[ne] = temp;
}
}
else if (strcmp(csa->field, "n") == 0)
{ /* symbolic name descriptor */
read_field(csa);
if (strcmp(csa->field, "p") == 0)
{ /* problem name */
read_field(csa);
if (P->name != NULL)
error(csa, "duplicate problem name");
glp_set_prob_name(P, csa->field);
}
else if (strcmp(csa->field, "z") == 0)
{ /* objective name */
read_field(csa);
if (P->obj != NULL)
error(csa, "duplicate objective name");
glp_set_obj_name(P, csa->field);
}
else if (strcmp(csa->field, "i") == 0)
{ /* row name */
read_field(csa);
if (str2int(csa->field, &i) != 0)
error(csa, "row number missing or invalid");
if (!(1 <= i && i <= m))
error(csa, "row number out of range");
read_field(csa);
if (P->row[i]->name != NULL)
error(csa, "duplicate row name");
glp_set_row_name(P, i, csa->field);
}
else if (strcmp(csa->field, "j") == 0)
{ /* column name */
read_field(csa);
if (str2int(csa->field, &j) != 0)
error(csa, "column number missing or invalid");
if (!(1 <= j && j <= n))
error(csa, "column number out of range");
read_field(csa);
if (P->col[j]->name != NULL)
error(csa, "duplicate column name");
glp_set_col_name(P, j, csa->field);
}
else
error(csa, "object designator missing or invalid");
}
else if (strcmp(csa->field, "e") == 0)
break;
else
error(csa, "line designator missing or invalid");
end_of_line(csa);
}
if (ne < nnz)
error(csa, "too few constraint coefficient descriptors");
xassert(ne == nnz);
k = glp_check_dup(m, n, ne, ia, ja);
xassert(0 <= k && k <= nnz);
if (k > 0)
{ csa->count = ln[k];
error(csa, "duplicate constraint coefficient");
}
glp_load_matrix(P, ne, ia, ja, ar);
/* print some statistics */
if (P->name != NULL)
xprintf("Problem: %s\n", P->name);
if (P->obj != NULL)
xprintf("Objective: %s\n", P->obj);
xprintf("%d row%s, %d column%s, %d non-zero%s\n",
m, m == 1 ? "" : "s", n, n == 1 ? "" : "s", nnz, nnz == 1 ?
"" : "s");
if (glp_get_num_int(P) > 0)
{ int ni = glp_get_num_int(P);
int nb = glp_get_num_bin(P);
if (ni == 1)
{ if (nb == 0)
xprintf("One variable is integer\n");
else
xprintf("One variable is binary\n");
}
else
{ xprintf("%d integer variables, ", ni);
if (nb == 0)
xprintf("none");
else if (nb == 1)
xprintf("one");
else if (nb == ni)
xprintf("all");
else
xprintf("%d", nb);
xprintf(" of which %s binary\n", nb == 1 ? "is" : "are");
}
}
xprintf("%d lines were read\n", csa->count);
/* problem data has been successfully read */
glp_sort_matrix(P);
ret = 0;
done: if (csa->fp != NULL) glp_close(csa->fp);
if (rf != NULL) xfree(rf);
if (cf != NULL) xfree(cf);
if (ln != NULL) xfree(ln);
if (ia != NULL) xfree(ia);
if (ja != NULL) xfree(ja);
if (ar != NULL) xfree(ar);
if (ret) glp_erase_prob(P);
return ret;
}
int main(int argc, char * argv[]) {
int i,j;
time(&initial);
srand(SEED);
/* Default values */
outFile = stdout;
maxAlpha = 2;
maxIter = 100;
maxTime = 30;
randomSeed = SEED;
simpleOutput = 0;
/* Read arguments */
if( argc > 7 )
argc = 7;
switch(argc) {
case 7:
simpleOutput = atoi(argv[6]);
case 6:
if( !(randomSeed = atoi(argv[5])) )
leave(argv[0]);
case 5:
if( !(maxTime = atoi(argv[4])) )
leave(argv[0]);
case 4:
if( !(maxIter = atoi(argv[3])) )
leave(argv[0]);
case 3:
if( !(maxAlpha = atoi(argv[2])) )
leave(argv[0]);
case 2:
if( simpleOutput ) {
if( !(outFile = fopen(argv[1],"a")) )
leave(argv[0]);
break;
}
if( !(outFile = fopen(argv[1],"w")) )
leave(argv[0]);
}
readInput(stdin);
/* Initiate positions */
for( i = 0 ; i < n ; ++i ) {
pOrd[i].ideal = planes[i].ideal;
pOrd[i].pos = i;
}
qsort (pOrd, n, sizeof(struct planeOrder), compIdealT);
for( i = 0 ; i < n ; ++i ) {
planes[pOrd[i].pos].pos = i;
}
/* Create lp instance */
glp_prob * Prob;
Prob = glp_create_prob();
glp_set_prob_name(Prob, "Airplane Landing Problem");
glp_set_obj_name(Prob, "Cost");
/* Create basic constraints */
for( i = 0 ; i < n ; ++i ) {
addBasicRestriction(Prob,i);
}
glp_create_index(Prob);
/* Create separation constraints and order variables (&ij) if necessary */
for( i = 0 ; i < n ; ++i ) {
for( j = i+1 ; j < n ; ++j ) {
if( planes[i].latest >= planes[j].earliest &&
planes[j].latest >= planes[i].earliest ) {
addOrderConstraint(Prob,i,j);
} else if ( planes[i].latest < planes[j].earliest &&
planes[i].latest + planes[i].sep[j] >= planes[j].earliest ) {
addSeparationConstraint(Prob, i, j);
} else if ( planes[j].latest < planes[i].earliest &&
planes[j].latest + planes[j].sep[i] >= planes[i].earliest ) {
addSeparationConstraint(Prob, j, i);
}
}
}
/* Write problem in MPS format so glpsol can (try to) solve it */
glp_write_mps(Prob, GLP_MPS_FILE, NULL,"mpsProblem.txt");
glp_delete_index(Prob);
glp_create_index(Prob);
/* GRASP */
/* Data to handle glp solving, time checking and solution generating */
glp_smcp * param = malloc(sizeof(glp_smcp));
glp_init_smcp(param);
param->msg_lev = GLP_MSG_ERR;
int solution[MAXSIZE], timeAux[MAXSIZE], t;
double currResult = DBL_MAX, bestResult = DBL_MAX;
alpha = 0;
time_t start, curr;
time(&start);
for( t = 0 ; t < maxIter ; ++t ) {
/* Greedy solution generation */
while(createSolution(solution,timeAux,0))
alpha = n;
/* Building the right constraints */
mapSolution(Prob,solution);
/* Solving with glpsol */
param->presolve = GLP_ON;
glp_simplex(Prob,param);
param->presolve = GLP_OFF;
currResult = glp_get_obj_val(Prob);
/* Local search using the first increase */
for( i = 0 ; i < n-1 ; ++i ) {
/* Swap two adjacent planes */
swapConstraint(Prob,i,solution,0);
glp_simplex(Prob,param);
/* Check for improvements */
if( GLP_OPT == glp_get_status(Prob) && glp_get_obj_val(Prob) < currResult ) {
currResult = glp_get_obj_val(Prob);
/* Changing the solution */
int swp;
swp = solution[i];
solution[i] = solution[i+1];
solution[i+1] = swp;
/* Restarting */
i = -1;
} else
swapConstraint(Prob,i,solution,1);
}
/* Checking improvements */
if( bestResult > currResult ) {
bestResult = currResult;
for( i = 0 ; i < n ; ++i )
planes[solution[i]].pos = i;
}
/* Choosing alpha */
alpha = rand()%(maxAlpha+1);
/* Is our time up? */
time(&curr);
if( difftime(curr,start) > maxTime )
break;
}
/* Print Answer */
printResult(Prob, stdout);
if( outFile ) {
printResult(Prob, outFile);
fclose(outFile);
}
return 0;
}
void c_glp_set_obj_name(glp_prob *lp, const char *name){
glp_set_obj_name(lp, name);
}
