int main(int argc, char **argv)
{
population *pop=NULL; /* Population structure. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
random_seed(23091975);
pop = ga_genesis_char(
120, /* const int population_size */
1, /* const int num_chromo */
(int) strlen(target_text), /* const int len_chromo */
struggle_generation_hook, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
struggle_adaptation, /* GAadapt adapt */
ga_select_one_sus, /* GAselect_one select_one */
ga_select_two_sus, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* GAcrossover crossover */
NULL, /* GAreplace replace */
NULL /* vpointer User data */
);
ga_population_set_parameters(
pop, /* population *pop */
GA_SCHEME_LAMARCK_CHILDREN, /* const ga_scheme_type scheme */
GA_ELITISM_PARENTS_DIE, /* const ga_elitism_type elitism */
0.8, /* const double crossover */
0.05, /* const double mutation */
0.0 /* const double migration */
);
if ( ga_evolution( pop, 1000 )<1000 )
{
printf("The evolution was stopped because the termination criteria were met.\n" );
}
else
{
printf("The evolution was stopped because the maximum number of generations were performed.\n" );
}
printf( "The final solution with score %f was:\n",
ga_get_entity_from_rank(pop,0)->fitness );
beststring = ga_chromosome_char_to_string(pop, ga_get_entity_from_rank(pop,0), beststring, &beststrlen);
printf("%s\n", beststring);
printf( "Total number of fitness evaluations: %ld\n", evaluation_count );
ga_extinction(pop);
s_free(beststring);
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
int i; /* Loop over runs. */
population *pop=NULL; /* Population of solutions. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
for (i=0; i<50; i++)
{
random_seed(i);
pop = ga_genesis_char(
120, /* const int population_size */
1, /* const int num_chromo */
(int) strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
NULL, /* GAadapt adapt */
ga_select_one_sus, /* GAselect_one select_one */
ga_select_two_sus, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* 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_DIE, /* const ga_elitism_type elitism */
0.9, /* double crossover */
0.2, /* double mutation */
0.0 /* double migration */
);
ga_evolution_threaded(
pop, /* population *pop */
500 /* const int max_generations */
);
printf( "The final solution with seed = %d was:\n", i );
beststring = ga_chromosome_char_to_string(pop, ga_get_entity_from_rank(pop,0), beststring, &beststrlen);
printf("%s\n", beststring);
printf( "With score = %f\n", ga_entity_get_fitness(ga_get_entity_from_rank(pop,0)) );
ga_extinction(pop);
}
s_free(beststring);
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
population *pop=NULL; /* Population of solutions. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
entity *solution; /* Solution to problem. */
int num_iterations; /* Number of iterations required. */
random_seed(23091975);
pop = ga_genesis_char(
100, /* const int population_size */
1, /* const int num_chromo */
strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
struggle_seed, /* GAseed seed */
NULL, /* GAadapt adapt */
NULL, /* GAselect_one select_one */
NULL, /* GAselect_two select_two */
NULL, /* GAmutate mutate */
NULL, /* GAcrossover crossover */
NULL, /* GAreplace replace */
NULL /* vpointer User data */
);
ga_population_set_search_parameters(pop, struggle_scan_chromosome);
solution = ga_get_free_entity(pop);
num_iterations = ga_search(
pop, /* population *pop */
solution /* entity *entity */
);
printf( "The final solution was:\n");
beststring = ga_chromosome_char_to_string(pop, solution, beststring, &beststrlen);
printf("%s\n", beststring);
printf( "With score = %f\n", ga_entity_get_fitness(solution) );
printf( "This required %d iterations\n", num_iterations);
ga_extinction(pop);
s_free(beststring);
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
population *pop=NULL; /* Population of solutions. */
char *filename_in=NULL; /* Input filename. */
char *filename_out=NULL; /* Output filename. */
int i; /* Loop variable over command-line arguments. */
int generations=10; /* Number of generations to perform. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
random_seed(42);
/*
* Parse command-line. Expect '-i FILENAME' for a population to read,
* otherwise a new population will be created.
* '-o FILENAME' is absolutely required to specify a file to write to.
* If we don't get these, then we will write the options.
*/
if (argc<2)
{
write_usage();
exit(0);
}
for (i=1; i<argc; i++)
{
if (strcmp(argv[i], "-i")==0)
{ /* Read pop. */
i++;
if (i==argc)
{
printf("Input filename not specified.\n");
write_usage();
exit(0);
}
filename_in = argv[i];
printf("Input filename set to \"%s\"\n", filename_in);
}
else if (strcmp(argv[i], "-o")==0)
{ /* Out pop. */
i++;
if (i==argc)
{
printf("Output filename not specified.\n");
write_usage();
exit(0);
}
filename_out = argv[i];
printf("Output filename set to \"%s\"\n", filename_out);
}
else if (strcmp(argv[i], "-n")==0)
{ /* Number of generations requested. */
i++;
if (i==argc)
{
printf("Number of generations not specified.\n");
write_usage();
exit(0);
}
generations = atoi(argv[i]);
printf("Number of generations set to %d.\n", generations);
}
else
{ /* Error parsing args. */
printf("Unable to parse command-line argument \"%s\"\n", argv[i]);
write_usage();
exit(0);
}
}
/*
* Check that we had the required inputs.
*/
if (filename_out == NULL)
{
printf("No output filename was specified.\n");
write_usage();
exit(0);
}
/*
* Read or create population.
*/
if (filename_in == NULL)
{
pop = ga_genesis_char(
40, /* const int population_size */
1, /* const int num_chromo */
strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
NULL, /* GAadapt adapt */
ga_select_one_roulette, /* GAselect_one select_one */
ga_select_two_roulette, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* 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 */
1.0, /* double crossover */
0.1, /* double mutation */
0.0 /* double migration */
);
}
else
{
pop = ga_population_read(filename_in);
pop->evaluate = struggle_score; /* Custom functions can't be saved and
* therefore "pop->evaluate" must be
* defined manually. Likewise, if a
* custom crossover routine was used, for
* example, then that would also need
* to be manually defined here.
*/
}
ga_evolution(
pop, /* population *pop */
generations /* const int max_generations */
);
printf("The final solution with seed = %d was:\n", i);
beststring = ga_chromosome_char_to_string(pop, ga_get_entity_from_rank(pop,0), beststring, &beststrlen);
printf("%s\n", beststring);
printf("With score = %f\n", ga_entity_get_fitness(ga_get_entity_from_rank(pop,0)) );
ga_population_write(pop, filename_out);
printf("Population has been saved as \"%s\"\n", filename_out);
ga_extinction(pop);
s_free(beststring);
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
int i; /* Loop over populations. */
population *pop[GA_STRUGGLE_NUM_POPS]; /* Array of populations. */
population *slavepop; /* Population for slave calculations. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
int rank; /* MPI rank. */
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
printf("Process %d initialised (rank %d)\n", getpid(), rank);
random_seed(42);
if (rank != 0)
{ /* This is a slave process. */
/*
* A population is created so that the callbacks are defined. Evolution doesn't
* occur with this population, so population_size can be zero. In such a case,
* no entities are ever seeded, so there is no significant overhead.
* Strictly, several of these callbacks are not needed on the slave processes, but
* their definition doesn't have any adverse effects.
*/
slavepop = ga_genesis_char(
0, /* const int population_size */
1, /* const int num_chromo */
(int) strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
NULL, /* GAadapt adapt */
ga_select_one_sus, /* GAselect_one select_one */
ga_select_two_sus, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* GAcrossover crossover */
NULL, /* GAreplace replace */
NULL /* vpointer User data */
);
printf("DEBUG: Attaching process %d\n", rank);
ga_attach_mpi_slave( slavepop ); /* The slaves halt here until ga_detach_mpi_slaves(), below, is called. */
}
else
{
/*
* This is the master process. Other than calling ga_evolution_mpi() instead
* of ga_evolution(), there are no differences between this code and the usual
* GAUL invocation.
*/
for (i=0; i<GA_STRUGGLE_NUM_POPS; i++)
{
pop[i] = ga_genesis_char(
80, /* const int population_size */
1, /* const int num_chromo */
(int) strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
NULL, /* GAadapt adapt */
ga_select_one_sus, /* GAselect_one select_one */
ga_select_two_sus, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* GAcrossover crossover */
NULL, /* GAreplace replace */
NULL /* vpointer User data */
);
ga_population_set_parameters( pop[i], GA_SCHEME_DARWIN, GA_ELITISM_PARENTS_DIE, 0.75, 0.25, 0.001 );
}
ga_evolution_archipelago_mpi( GA_STRUGGLE_NUM_POPS, pop, 250 );
for (i=0; i<GA_STRUGGLE_NUM_POPS; i++)
{
printf( "The best solution on island %d with score %f was:\n",
i, ga_get_entity_from_rank(pop[i],0)->fitness );
beststring = ga_chromosome_char_to_string(pop[i], ga_get_entity_from_rank(pop[i],0), beststring, &beststrlen);
printf("%s\n", beststring);
ga_extinction(pop[i]);
}
s_free(beststring);
ga_detach_mpi_slaves(); /* Allow all slave processes to continue. */
}
MPI_Finalize();
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
population *popd=NULL; /* Population for Darwinian evolution. */
population *popb=NULL; /* Population for Baldwinian evolution. */
population *popl=NULL; /* Population for Lamarckian evolution. */
char *beststring=NULL; /* Human readable form of best solution. */
size_t beststrlen=0; /* Length of beststring. */
random_seed(23091975);
popd = ga_genesis_char(
150, /* const int population_size */
1, /* const int num_chromo */
(int) strlen(target_text), /* const int len_chromo */
NULL, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
struggle_score, /* GAevaluate evaluate */
ga_seed_printable_random, /* GAseed seed */
struggle_adaptation, /* GAadapt adapt */
ga_select_one_sus, /* GAselect_one select_one */
ga_select_two_sus, /* GAselect_two select_two */
ga_mutate_printable_singlepoint_drift, /* GAmutate mutate */
ga_crossover_char_allele_mixing, /* GAcrossover crossover */
NULL, /* GAreplace replace */
NULL /* vpointer User data */
);
ga_population_set_parameters(
popd, /* population *pop */
GA_SCHEME_DARWIN, /* const ga_scheme_type scheme */
GA_ELITISM_PARENTS_DIE, /* const ga_elitism_type elitism */
0.9, /* const double crossover */
0.1, /* const double mutation */
0.0 /* const double migration */
);
/*
* Make exact copies of the populations, except modify
* their evolutionary schemes.
*/
popb = ga_population_clone(popd);
ga_population_set_scheme(popb, GA_SCHEME_BALDWIN_CHILDREN);
popl = ga_population_clone(popd);
ga_population_set_scheme(popl, GA_SCHEME_LAMARCK_CHILDREN);
/*
* Evolve each population in turn.
*/
ga_evolution(
popd, /* population *pop */
600 /* const int max_generations */
);
printf( "The final solution with Darwinian evolution with score %f was:\n",
ga_get_entity_from_rank(popd,0)->fitness );
beststring = ga_chromosome_char_to_string(popd, ga_get_entity_from_rank(popd,0), beststring, &beststrlen);
printf("%s\n", beststring);
ga_evolution(
popb, /* population *pop */
300 /* const int max_generations */
);
printf( "The final solution with Baldwinian evolution with score %f was:\n",
ga_get_entity_from_rank(popb,0)->fitness );
beststring = ga_chromosome_char_to_string(popb, ga_get_entity_from_rank(popb,0), beststring, &beststrlen);
printf("%s\n", beststring);
ga_evolution(
popl, /* population *pop */
300 /* const int max_generations */
);
printf( "The final solution with Lamarckian evolution with score %f was:\n",
ga_get_entity_from_rank(popl,0)->fitness );
beststring = ga_chromosome_char_to_string(popl, ga_get_entity_from_rank(popl,0), beststring, &beststrlen);
printf("%s\n", beststring);
/* Deallocate population structures. */
ga_extinction(popd);
ga_extinction(popb);
ga_extinction(popl);
/* Deallocate string buffer. */
s_free(beststring);
exit(EXIT_SUCCESS);
}
int main(int argc, char **argv)
{
population *pop; /* Population of solutions. */
fitting_data_t data; /* Training data. */
FILE * fData;
random_seed(time(NULL));
double params_d[4];
double x;
// fitting
if(argc >= 3 && strcmp(argv[1], "fit") == 0)
{
pop = ga_genesis_char(
100, /* const int population_size */
1, /* const int num_chromo */
3, /* const int len_chromo */
fitting_generation_callback, /* GAgeneration_hook generation_hook */
NULL, /* GAiteration_hook iteration_hook */
NULL, /* GAdata_destructor data_destructor */
NULL, /* GAdata_ref_incrementor data_ref_incrementor */
fitting_score, /* GAevaluate evaluate */
//fitting_seed, /* GAseed seed */
ga_seed_char_random,
NULL, /* GAadapt adapt */
//ga_select_one_linearrank,
ga_select_one_random, /* GAselect_one select_one */
ga_select_two_random, /* GAselect_two select_two */
ga_mutate_char_singlepoint_randomize,/* GAmutate mutate */
ga_crossover_char_allele_mixing,/* 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_DIE, /* const ga_elitism_type elitism */
0.8, /* double crossover */
0.8, /* double mutation */
0.0 /* double migration */
);
fData = fopen("data", "r");
debug_message("Begin Get Data\n");
get_data(fData, &data);
pop->data = &data;
debug_message("Done Get Data\n");
debug_message("Begin Evolution\n");
ga_evolution(
pop, /* population *pop */
200 /* const int max_generations */
);
debug_message("Done Evolution\n");
ga_extinction(pop);
}
// plot
else if(argc >= 5 && strcmp(argv[1], "plot")==0)
{
params_d[0] = E_GIVEN;
params_d[1] = atof(argv[2]);
params_d[2] = atof(argv[3]);
params_d[3] = atof(argv[4]);
for(x = 0; x < 10; x += 0.01)
{
fprintf(stdout, "%lf %lf\n", x, target_function(x, params_d));
}
}
else
{
fprintf(stdout, "usage: %s [plot/fit] [params]\n", argv[0]);
}
}