def genetic_algorithm(F_time_list, int_result2, max_iteration=100): population_size = 10 chromosome_length = 10 population = [''.join([random.choice(['0', '1']) for _ in range(chromosome_length)]) for _ in range(population_size)] for i in range(max_iteration): fitness_scores = [fitness_score(chromosome, F_time_list, int_result2) for chromosome in population] if any([score == 0 for score in fitness_scores]): return population[fitness_scores.index(0)] parents = roulette_selection(population, fitness_scores) children = two_point_crossover(parents[0], parents[1]) mutated_children = [mutation(child) for child in children] population = population + mutated_children best_chromosome = max(population, key=lambda x: fitness_score(x, f_points, pf_lengths)) return best_chromosome print(genetic_algorithm(F_time_list, int_result2))

在你提供的代码中，存在一些错误：

1. `for` 循环缺少缩进，需要将 `for` 循环和后面的代码块缩进到同一层级。

2. `f_points` 和 `pf_lengths` 未定义，可能会导致 NameError 错误。你需要检查一下这两个变量是否在代码中定义过。

3. `print` 语句和 `genetic_algorithm` 函数之间有空格，这会导致语法错误。

下面是修改后的代码：

def genetic_algorithm(F_time_list, int_result2, max_iteration=100):
    population_size = 10
    chromosome_length = 10
    population = [''.join([random.choice(['0', '1']) for _ in range(chromosome_length)]) for _ in range(population_size)]
    
    for i in range(max_iteration):
        fitness_scores = [fitness_score(chromosome, F_time_list, int_result2) for chromosome in population]
        if any([score == 0 for score in fitness_scores]):
            return population[fitness_scores.index(0)]
        parents = roulette_selection(population, fitness_scores)
        children = two_point_crossover(parents[0], parents[1])
        mutated_children = [mutation(child) for child in children]
        population = population + mutated_children
        best_chromosome = max(population, key=lambda x: fitness_score(x, f_points, pf_lengths))
    
    return best_chromosome

print(genetic_algorithm(F_time_list, int_result2))

请注意，由于我不知道你的完整代码，因此这只是一个基于你提供的代码的修改建议，并不能保证代码能够完全运行。