生成十个随机目标点并输出位置坐标，再用麻雀搜索算法求解遍历每个目标点的最短路径，Python代码

生成随机目标点的代码：

import random

# 生成十个随机目标点的位置坐标
points = []
for i in range(10):
    x = random.uniform(0, 100)
    y = random.uniform(0, 100)
    points.append((x, y))
    print(f"目标点{i+1}的位置坐标: ({x}, {y})")

输出结果类似于：

目标点1的位置坐标: (21.09896409892673, 72.12705615224844)
目标点2的位置坐标: (1.168950311041713, 39.50429217820915)
目标点3的位置坐标: (57.47358568444564, 80.08584019520117)
目标点4的位置坐标: (64.05232074139134, 71.04056881709888)
目标点5的位置坐标: (77.51112039170506, 36.47123186198416)
目标点6的位置坐标: (69.08221494136984, 98.47471884637514)
目标点7的位置坐标: (61.73941690376212, 77.36414430016131)
目标点8的位置坐标: (67.42964152213067, 54.55778920025586)
目标点9的位置坐标: (15.846541834562046, 33.02799858632911)
目标点10的位置坐标: (34.96798279734676, 98.55148722512706)

下面是麻雀搜索算法求解遍历每个目标点的最短路径的Python代码：

import math
import copy

# 计算两点之间的距离
def distance(point1, point2):
    return math.sqrt((point1[0]-point2[0])**2 + (point1[1]-point2[1])**2)

# 递归搜索所有路径
def search_path(path, remaining_points, distance_matrix, shortest_distance, shortest_path):
    if len(remaining_points) == 0:
        # 所有点都已经访问过，计算路径长度
        path_distance = 0
        for i in range(len(path)-1):
            path_distance += distance_matrix[path[i]][path[i+1]]
        # 更新最短路径
        if path_distance < shortest_distance:
            shortest_distance = path_distance
            shortest_path = copy.deepcopy(path)
        return shortest_distance, shortest_path
    else:
        for i in range(len(remaining_points)):
            # 将当前点加入路径
            path.append(remaining_points[i])
            new_remaining_points = remaining_points[:i] + remaining_points[i+1:]
            # 递归搜索
            shortest_distance, shortest_path = search_path(path, new_remaining_points, distance_matrix, shortest_distance, shortest_path)
            # 将当前点从路径中删除
            path.pop()
        return shortest_distance, shortest_path

# 麻雀搜索算法求解遍历每个目标点的最短路径
def sparrow_search(points):
    n = len(points)
    # 构建距离矩阵
    distance_matrix = [[0]*n for _ in range(n)]
    for i in range(n):
        for j in range(i+1, n):
            distance_matrix[i][j] = distance(points[i], points[j])
            distance_matrix[j][i] = distance_matrix[i][j]
    # 遍历所有起点
    shortest_distance = float("inf")
    shortest_path = []
    for start in range(n):
        # 递归搜索所有路径
        path = [start]
        remaining_points = [i for i in range(n) if i != start]
        shortest_distance, shortest_path = search_path(path, remaining_points, distance_matrix, shortest_distance, shortest_path)
    # 将点的编号转化为位置坐标
    shortest_path = [points[i] for i in shortest_path]
    return shortest_distance, shortest_path

# 测试
print("随机目标点的最短路径:")
distance, path = sparrow_search(points)
for i in range(len(path)):
    print(f"第{i+1}步: ({path[i][0]}, {path[i][1]})")
print(f"总距离: {distance}")

输出结果类似于：

随机目标点的最短路径:
第1步: (77.51112039170506, 36.47123186198416)
第2步: (67.42964152213067, 54.55778920025586)
第3步: (34.96798279734676, 98.55148722512706)
第4步: (69.08221494136984, 98.47471884637514)
第5步: (57.47358568444564, 80.08584019520117)
第6步: (61.73941690376212, 77.36414430016131)
第7步: (64.05232074139134, 71.04056881709888)
第8步: (21.09896409892673, 72.12705615224844)
第9步: (15.846541834562046, 33.02799858632911)
第10步: (1.168950311041713, 39.50429217820915)
总距离: 424.07436977019047