帮我用python语言编写一段遗传算法代码

好的，我会为您提供关于遗传算法的代码实现。以下是一个简单的遗传算法的示例，用于求解一个函数的最优解。在这个示例中，我们将最小化函数 f(x) = x^2，将个体定义为实数，最大进化代数为100，种群大小为100，交叉概率为0.8，变异概率为0.1。

import random

def fitness(individual):
    return individual**2

def generate_population(pop_size):
    population = []
    for i in range(pop_size):
        population.append(random.uniform(-10, 10))
    return population

def selection(population):
    selected = random.sample(population, 2)
    return sorted(selected, key=lambda x: fitness(x))[0]

def crossover(parent_1, parent_2):
    if random.random() < crossover_prob:
        return (parent_1 + parent_2) / 2
    else:
        return parent_1

def mutate(individual):
    if random.random() < mutation_prob:
        return individual + random.uniform(-1, 1)
    else:
        return individual

def genetic_algorithm(pop_size, gens):
    population = generate_population(pop_size)
    for i in range(gens):
        new_population = []
        for j in range(pop_size):
            parent_1 = selection(population)
            parent_2 = selection(population)
            offspring = crossover(parent_1, parent_2)
            offspring = mutate(offspring)
            new_population.append(offspring)
        population = new_population
    return min(population, key=lambda x: fitness(x))

if __name__ == '__main__':
    pop_size = 100
    gens = 100
    crossover_prob = 0.8
    mutation_prob = 0.1
    result = genetic_algorithm(pop_size, gens)
    print("最优解为:", result)

以上是一个遗传算法的简单实现，您可以根据自己的需求修改代码并调整参数。希望能对您有所帮助！