智能仓储系统路径规划Python代码

智能仓储系统的路径规划通常涉及算法如Dijkstra、A*搜索或者基于机器学习的路径优化。以下是使用Python实现Dijkstra算法的一个简单示例，这个算法常用于寻找从仓库入口到存储单元的最短路径：

import heapq

def dijkstra(graph, start):
    distances = {node: float('infinity') for node in graph}
    distances[start] = 0
    queue = [(0, start)]
    
    while queue:
        current_distance, current_node = heapq.heappop(queue)
        
        if current_distance > distances[current_node]:
            continue
        
        for neighbor, weight in graph[current_node].items():
            distance = current_distance + weight
            
            if distance < distances[neighbor]:
                distances[neighbor] = distance
                heapq.heappush(queue, (distance, neighbor))
                
    return distances

# 示例仓库地图可以用字典表示，键是节点，值是一个字典，包含邻居和权重
warehouse_map = {
    'A': {'B': 5, 'C': 3},
    'B': {'A': 5, 'D': 7},
    'C': {'A': 3, 'E': 4},
    'D': {'B': 7, 'E': 6},
    'E': {'C': 4, 'D': 6}
}

shortest_path = dijkstra(warehouse_map, 'A')
print("从'A'到其他节点的最短路径:", shortest_path)