test_ga.c

关于遗传算法的一些见地。特别是关于简单遗传程序设计的实现。

/**********************************************************************
  test_ga.c
 **********************************************************************

  test_ga - Test program for GAUL.
  Copyright ©2002-2005, Stewart Adcock <[e-mail]>
  All rights reserved.

  The latest version of this program should be available at:
  http://gaul.sourceforge.net/

  This program is free software; you can redistribute it and/or modify
  it under the terms of the GNU General Public License as published by
  the Free Software Foundation; either version 2 of the License, or
  (at your option) any later version.  Alternatively, if your project
  is incompatible with the GPL, I will probably agree to requests
  for permission to use the terms of any other license.

  This program is distributed in the hope that it will be useful, but
  WITHOUT ANY WARRANTY WHATSOEVER.

  A full copy of the GNU General Public License should be in the file
  "COPYING" provided with this distribution; if not, see:
  http://www.gnu.org/

 **********************************************************************

  Synopsis:	Test program for GAUL's basic genetic algorithm.

		This program aims to solve a function of the form
		(0.75-A)+(0.95-B)^2+(0.23-C)^3+(0.71-D)^4 = 0

 **********************************************************************/

#include "gaul.h"


/**********************************************************************
  test_score()
  synopsis:	Fitness function.
  parameters:
  return:
  updated:	25 Nov 2002
 **********************************************************************/

boolean test_score(population *pop, entity *entity)
  {
  double		A, B, C, D;	/* Parameters. */

  A = ((double *)entity->chromosome[0])[0];
  B = ((double *)entity->chromosome[0])[1];
  C = ((double *)entity->chromosome[0])[2];
  D = ((double *)entity->chromosome[0])[3];

  entity->fitness = -(fabs(0.75-A)+SQU(0.95-B)+fabs(CUBE(0.23-C))+FOURTH_POW(0.71-D));

  return TRUE;
  }


/**********************************************************************
  test_generation_callback()
  synopsis:	Generation callback
  parameters:
  return:
  updated:	25 Nov 2002
 **********************************************************************/

boolean test_generation_callback(int generation, population *pop)
  {

  printf( "%d: A = %f B = %f C = %f D = %f (fitness = %f)\n",
            generation,
            ((double *)pop->entity_iarray[0]->chromosome[0])[0],
            ((double *)pop->entity_iarray[0]->chromosome[0])[1],
            ((double *)pop->entity_iarray[0]->chromosome[0])[2],
            ((double *)pop->entity_iarray[0]->chromosome[0])[3],
            pop->entity_iarray[0]->fitness );

  return TRUE;
  }


/**********************************************************************
  test_seed()
  synopsis:	Seed genetic data.
  parameters:	population *pop
		entity *adam
  return:	success
  last updated: 25 Nov 2002
 **********************************************************************/

boolean test_seed(population *pop, entity *adam)
  {

/* Checks. */
  if (!pop) die("Null pointer to population structure passed.");
  if (!adam) die("Null pointer to entity structure passed.");

/* Seeding. */
  ((double *)adam->chromosome[0])[0] = random_double(2.0);
  ((double *)adam->chromosome[0])[1] = random_double(2.0);
  ((double *)adam->chromosome[0])[2] = random_double(2.0);
  ((double *)adam->chromosome[0])[3] = random_double(2.0);

  return TRUE;
  }


/**********************************************************************
  main()
  synopsis:	Main function.
  parameters:
  return:
  updated:	25 Nov 2002
 **********************************************************************/

int main(int argc, char **argv)
  {
  population		*pop;			/* Population of solutions. */

  random_seed(23091975);

  pop = ga_genesis_double(
       200,			/* const int              population_size */
       1,			/* const int              num_chromo */
       4,			/* const int              len_chromo */
       test_generation_callback,/* GAgeneration_hook      generation_hook */
       NULL,			/* GAiteration_hook       iteration_hook */
       NULL,			/* GAdata_destructor      data_destructor */
       NULL,			/* GAdata_ref_incrementor data_ref_incrementor */
       test_score,		/* GAevaluate             evaluate */
       test_seed,		/* GAseed                 seed */
       NULL,			/* GAadapt                adapt */
       ga_select_one_bestof2,	/* GAselect_one           select_one */
       ga_select_two_bestof2,	/* GAselect_two           select_two */
       ga_mutate_double_singlepoint_drift,	/* GAmutate               mutate */
       ga_crossover_double_doublepoints,	/* GAcrossover            crossover */
       NULL,			/* GAreplace              replace */
       NULL			/* vpointer	User data */
            );

  ga_population_set_parameters(
       pop,				/* population      *pop */
       GA_SCHEME_DARWIN,		/* const ga_scheme_type     scheme */
       GA_ELITISM_PARENTS_SURVIVE,	/* const ga_elitism_type   elitism */
       0.8,				/* double  crossover */
       0.2,				/* double  mutation */
       0.0      		        /* double  migration */
                              );

  ga_evolution(
       pop,				/* population	*pop */
       500				/* const int	max_generations */
              );

  ga_extinction(pop);

  exit(EXIT_SUCCESS);
  }