生成一个布谷鸟算法的代码

以下是一个简单的布谷鸟算法的 Python 代码实现。您可以将其用作参考并扩展它以满足您的需求。

import random

# 参数设置
population_size = 20
max_generation = 100
num_variables = 10
low_bound = -10
up_bound = 10

# 布谷鸟生成函数
def generate_bird():
    bird = {
        "position": [random.uniform(low_bound, up_bound) for _ in range(num_variables)],
        "fitness": None,
        "num_flights": 0
    }
    return bird

# 评估函数
def evaluate_bird(bird):
    # 您的评估函数代码在这里
    return bird["fitness"]

# 布谷鸟搜索函数
def cuckoo_search():
    # 初始化种群
    population = [generate_bird() for _ in range(population_size)]

    # 计算每个布谷鸟的适应度
    for bird in population:
        bird["fitness"] = evaluate_bird(bird)

    # 开始搜索
    generation = 0
    while generation < max_generation:
        # 选择一个随机的布谷鸟
        random_bird_index = random.randint(0, population_size-1)
        random_bird = population[random_bird_index]

        # 生成新的布谷鸟并计算适应度
        new_bird = generate_bird()
        new_bird["fitness"] = evaluate_bird(new_bird)

        # 如果新的布谷鸟更优，则替换当前布谷鸟
        if new_bird["fitness"] > random_bird["fitness"]:
            population[random_bird_index] = new_bird

        # 对当前种群按适应度排序
        population = sorted(population, key=lambda x: x["fitness"], reverse=True)

        # 随机替换部分布谷鸟
        num_replaced_birds = int(0.2 * population_size)
        for i in range(num_replaced_birds):
            population[-(i+1)] = generate_bird()

        # 增加布谷鸟的飞行次数
        for bird in population:
            bird["num_flights"] += 1

        # 增加代数
        generation += 1

    # 返回最优布谷鸟
    return population[0]