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/*------------------------------------------------------------------------
*
* geqo_cx.c--
*
* cycle crossover [CX] routines;
* CX operator according to Oliver et al
* (Proc 2nd Int'l Conf on GA's)
*
* $Id: geqo_cx.c,v 1.1 1997/02/19 12:56:48 scrappy Exp $
*
*-------------------------------------------------------------------------
*/
/* contributed by:
=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=
* Martin Utesch * Institute of Automatic Control *
= = University of Mining and Technology =
* utesch@aut.tu-freiberg.de * Freiberg, Germany *
=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=
*/
/* the cx algorithm is adopted from Genitor : */
/*************************************************************/
/* */
/* Copyright (c) 1990 */
/* Darrell L. Whitley */
/* Computer Science Department */
/* Colorado State University */
/* */
/* Permission is hereby granted to copy all or any part of */
/* this program for free distribution. The author's name */
/* and this copyright notice must be included in any copy. */
/* */
/*************************************************************/
#include "postgres.h"
#include "nodes/pg_list.h"
#include "nodes/relation.h"
#include "nodes/primnodes.h"
#include "utils/palloc.h"
#include "utils/elog.h"
#include "optimizer/internal.h"
#include "optimizer/paths.h"
#include "optimizer/pathnode.h"
#include "optimizer/clauses.h"
#include "optimizer/cost.h"
#include "optimizer/geqo_gene.h"
#include "optimizer/geqo.h"
#include "optimizer/geqo_recombination.h"
#include "optimizer/geqo_random.h"
/* cx--
*
* cycle crossover
*/
int
cx(Gene *tour1, Gene *tour2, Gene *offspring, int num_gene, City *city_table)
{
int i, start_pos, curr_pos;
int count = 0;
int num_diffs = 0;
/* initialize city table */
for (i=1; i<=num_gene; i++) {
city_table[i].used = 0;
city_table[tour2[i-1]].tour2_position = i-1;
city_table[tour1[i-1]].tour1_position = i-1;
}
/* choose random cycle starting position */
start_pos = geqo_randint(num_gene - 1, 0);
/* child inherits first city */
offspring[start_pos] = tour1[start_pos];
/* begin cycle with tour1 */
curr_pos = start_pos;
city_table[(int) tour1[start_pos]].used = 1;
count++;
/* cx main part */
/* STEP 1 */
while (tour2[curr_pos] != tour1[start_pos]) {
city_table[(int) tour2[curr_pos]].used = 1;
curr_pos = city_table[(int) tour2[curr_pos]].tour1_position;
offspring[curr_pos] = tour1[curr_pos];
count++;
}
/* STEP 2 */
/* failed to create a complete tour */
if (count < num_gene) {
for (i=1; i<=num_gene; i++) {
if (!city_table[i].used) {
offspring[city_table[i].tour2_position] =
tour2[(int) city_table[i].tour2_position];
count++;
}
}
}
/* STEP 3 */
/* still failed to create a complete tour */
if (count < num_gene) {
/* count the number of differences between mom and offspring */
for (i=0; i<num_gene; i++)
if (tour1[i] != offspring[i]) num_diffs++;
}
return(num_diffs);
}
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