用Python写一段模拟退火算法代码，解决快递站点选址优化问题

好的，这是一段简单的模拟退火算法代码，可以解决快递站点选址优化问题：

import random
import math

def acceptance_probability(old_cost, new_cost, temperature):
    return math.exp((old_cost - new_cost) / temperature)

def simulated_annealing(cost_function, random_neighbor, temperature):
    current_solution = random_start()
    current_cost = cost_function(current_solution)
    best_solution = current_solution
    best_cost = current_cost

    while temperature > 1e-10:
        new_solution = random_neighbor(current_solution)
        new_cost = cost_function(new_solution)

        if acceptance_probability(current_cost, new_cost, temperature) > random.uniform(0, 1):
            current_solution = new_solution
            current_cost = new_cost
            if current_cost < best_cost:
                best_solution = current_solution
                best_cost = current_cost

        temperature *= 0.99

    return best_solution

其中，`cost_function` 函数需要自己定义，代表对当前解的评估，`random_neighbor` 函数也需要自己定义，代表如何生成当前解的邻居解。

希望这段代码对你有所帮助！