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from function import get_distances, get_value, result_plot, get_neighborsfrom random import randintdef r_opt(route): """利用2-opt算法对route进行改进,对当前路径所有不相邻的两点进行边边交换""" new_route = route[:] value = get_value(new_route, distances) for k1 in r.

代码如下：import numpy as npimport matplotlib.pyplot as pltepsilon = 0.8gamma = 0.1lr = 0.1distance = np.array([[0, 7, 6, 1, 3], [7, 0, 3, 7, 8], [6, 3, 0, 12, 11], [1, 7, 12, 0, 2], [3, 8, 11, 2, 0]])R_table = 11 - distancespace = [0, 1,

from function import get_distances, get_value, result_plot, get_neighborsfrom random import choice, random, randint# 算法参数N = 20000 # 迭代次数gama = 2 # 逃逸系数# 随机生成城市数据,城市序号为0,1，2,3...# city_coordinates = [(88, 16), (42, 76), (5, 76), (69, 13), (73, 5.

求解TSP问题的LK算法、LKH算法介绍及Python实现。目前正在进行中，欢迎一起讨论！！！

启发式算法与元启发式算法的区别主要在于是否存在“随机因素”，是否“problem dependent”。