用近似算法解旅行商问题的代码
时间: 2023-12-18 21:27:11 浏览: 45
是使用贪心算法解决旅行商问题的Python代码:
```python
import math
def tsp(points):
# 计算两点之间的距离
def distance(point1, point2):
x1, y1 = point1
x2, y2 = point2
return math.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2)
# 计算路径长度
def path_length(path):
return sum(distance(path[i], path[i+1]) for i in range(len(path)-1))
# 从起点开始,每次选择距离当前点最近的点作为下一个点
def nearest_neighbor(start, unvisited):
path = [start]
while unvisited:
nearest = min(unvisited, key=lambda x: distance(path[-1], x))
path.append(nearest)
unvisited.remove(nearest)
return path
# 从每个点开始,选择最短的路径
paths = [nearest_neighbor(p, set(points) - {p}) for p in points]
shortest_path = min(paths, key=path_length)
return shortest_path + [shortest_path[0]] # 回到起点
# 示例
points = [(0, 0), (1, 1), (2, 2), (3, 3)]
shortest_path = tsp(points)
print(shortest_path)
```
该代码使用贪心算法解决旅行商问题,即从起点开始,每次选择距离当前点最近的点作为下一个点,直到所有点都被访问过。然后从每个点开始,选择最短的路径。最终返回最短路径。