禁忌搜索算法卡车无人机路径代码

禁忌搜索算法是一种启发式搜索算法，它可以用来解决路径规划问题，包括卡车和无人机路径规划问题。下面是一个简单的禁忌搜索算法卡车无人机路径规划代码示例：

import numpy as np

# 随机生成地图
SIZE = 30
map = np.zeros((SIZE, SIZE))
for i in range(SIZE):
    for j in range(SIZE):
        if np.random.rand() > 0.8:
            map[i][j] = 1

# 定义路径规划类
class PathPlanning:
    def __init__(self, start, end, map):
        self.start = start
        self.end = end
        self.map = map
        self.tabu_list = set()
        self.best_path = []
    
    # 计算路径长度
    def path_length(self, path):
        length = 0
        for i in range(len(path)-1):
            x1, y1 = path[i]
            x2, y2 = path[i+1]
            length += np.sqrt((x2-x1)**2 + (y2-y1)**2)
        return length
    
    # 获取当前位置可行的下一步位置
    def get_next_positions(self, position):
        x, y = position
        next_positions = []
        if x > 0 and self.map[x-1][y] == 0:
            next_positions.append((x-1, y))
        if x < SIZE-1 and self.map[x+1][y] == 0:
            next_positions.append((x+1, y))
        if y > 0 and self.map[x][y-1] == 0:
            next_positions.append((x, y-1))
        if y < SIZE-1 and self.map[x][y+1] == 0:
            next_positions.append((x, y+1))
        return next_positions
    
    # 禁忌搜索算法
    def taboo_search(self):
        current_path = [self.start]
        current_length = self.path_length(current_path)
        self.best_path = current_path.copy()
        self.tabu_list.add(tuple(current_path))
        iter_count = 0
        while iter_count < 100:
            next_positions = self.get_next_positions(current_path[-1])
            next_path_length = []
            for position in next_positions:
                if tuple(current_path+[position]) not in self.tabu_list:
                    next_path = current_path + [position]
                    next_path_length.append((next_path, self.path_length(next_path)))
            if len(next_path_length) == 0:
                break
            next_path_length.sort(key=lambda x:x[1])
            next_path = next_path_length[0][0]
            next_length = next_path_length[0][1]
            if next_length < current_length:
                current_path = next_path
                current_length = next_length
                if current_length < self.path_length(self.best_path):
                    self.best_path = current_path.copy()
            self.tabu_list.add(tuple(next_path))
            if len(self.tabu_list) > 10:
                self.tabu_list.pop()
            iter_count += 1
        return self.best_path

# 测试代码
start = (0, 0)
end = (SIZE-1, SIZE-1)
planner = PathPlanning(start, end, map)
best_path = planner.taboo_search()
print("best path:", best_path)

该代码使用禁忌搜索算法来寻找从起点到终点的最短路径，其中地图随机生成。可以通过更改地图、起点和终点来测试不同情况下的路径规划效果。