/*
* 生成した2個体を母集団の中で適合度の悪い2個体を入れ替え
* この時、Population配列は適合度でソートされているものとする
*/
void swap_population(void)
{
Population[POP_SIZE - 1] = Children[0];
calc_fitness(POP_SIZE - 1);
Population[POP_SIZE - 2] = Children[1];
calc_fitness(POP_SIZE - 2);
}
int main()
{
srand(time(NULL));
data dat;
readfile(dat, "../../data/ks_19_0");
int items = dat[0].value;
population *pop, popalpha;
initialize_population(popalpha, items);
pop = &popalpha;
//print(*pop);
bat best = get_best(*pop);
int iterations = 200;
while(iterations > 0){
new_solutions(*pop,dat);
calc_fitness(*pop, dat);
if(getrand()> 0.5){
best = get_best(*pop);
move_bat(best, rand()%5, dat); // amplitude is 2
}
if(fitness(best, dat) > fitness((*pop).best, dat))
(*pop).best = best;
iterations--;
}
print(*pop);
}
int selection(int *p1, int *p2)
{
int i, j, num[2], point;
double sum, sum_of_fitness;
unsigned long seed = get_nano_seconds();
srand(seed);
sum_of_fitness = calc_fitness();
for (i=0; i<2; i++)
{
point = rand() % (int)(sum_of_fitness*1000000);
sum = 0;
for (j=1; j<=N; j++)
{
sum += sfitness[j]*1000000;
if ((double)point < sum)
{
num[i] = j;
break;
}
}
}
*p1 = num[0];
*p2 = num[1];
return 1;
}
/*
* 母集団内の全個体の適合度を計算
*/
void calc_fit_all(void)
{
int i;
for(i = 0; i < POP_SIZE; i++){
calc_fitness(i);
}
}
/*
* 母集団をランダムに初期化
*/
void init_chrom(void)
{
int i, j;
for(i = 0; i < POP_SIZE; i++){
for(j = 0; j < CHROM_LEN; j++){
// 遺伝子の各要素を0/1でランダムに初期化
Population[i].Chromsome[j] = rand() % 2;
}
calc_fitness(i);
}
}
int main(void)
{
int popsize = 0, max_iter = 0;
char target[128];
char str_buffer[64];
FILE *fp = fopen("conf", "r");
fscanf(fp, "%s %d", &str_buffer, &popsize);
fscanf(fp, "%s %s", &str_buffer, &target);
fscanf(fp, "%s %d", &str_buffer, &max_iter);
int target_length = strlen(target);
srand(time(NULL));
printf("Genetic Algorithm to find a user-specified target string\n");
printf("Quinn Thibeault - 2015\n");
printf("Target string: %s Length: %d\n", target, target_length);
printf("Population Size: %d\n", popsize);
printf("Maximum Iterations: %d\n\n", max_iter);
struct organism population[POPSIZE], buffer[POPSIZE];
struct organism *p_pop = population;
struct organism *p_buf = buffer;
init_population(p_pop, target_length);
init_population(p_buf, target_length);
gen_random_population(p_pop, target_length);
for(int i=0;i<ITER; ++i){
calc_fitness(p_pop, target, target_length);
sort_by_fitness(p_pop);
//print_most_fit(p_pop);
if(p_pop->fitness == 0){
printf("Number of generations: %d\n", i);
break;
}
regen_population(p_pop, p_buf, target_length);
swap(&p_pop, &p_buf);
}
print_most_fit(p_pop);
return 0;
}
// calculate fitness for all individuals
void GA::CalcFitness(void)
{
for(auto &individual : this->population_) {
calc_fitness(&individual);
}
}
