遗传算法select函数C实现

遗传算法的select函数是用来选择适应度高的个体，进入下一代的种群中。常见的select函数有轮盘赌选择、锦标赛选择、随机选择等。以下是一个简单的轮盘赌选择的C实现：

void select(double *fitness, int pop_size, int *selected)
{
    double sum_fitness = 0;
    double *accum_fitness = (double *)malloc(sizeof(double) * pop_size);
    accum_fitness[0] = fitness[0];
    for (int i = 1; i < pop_size; i++) {
        accum_fitness[i] = accum_fitness[i - 1] + fitness[i];
    }
    sum_fitness = accum_fitness[pop_size - 1];
    for (int i = 0; i < pop_size; i++) {
        double r = (double)rand() / RAND_MAX * sum_fitness;
        int j;
        for (j = 0; j < pop_size - 1; j++) {
            if (r <= accum_fitness[j]) {
                break;
            }
        }
        selected[i] = j;
    }
    free(accum_fitness);
}

其中，fitness是每个个体的适应度值，pop_size是种群大小，selected是被选择的个体的下标数组。函数首先计算出所有个体适应度值之和sum_fitness，然后根据每个个体的适应度值计算出累积适应度值accum_fitness。接着，函数生成一个随机数r，根据r在累积适应度值数组中找到对应的个体下标，将其加入到selected数组中。最后，释放累积适应度值数组的内存。