摘要
为优化物流配送路径,提升效率并降低时间成本,提出基于改进Floyd-Warshall算法的物流配送最优路径规划模型。通过对弗洛伊德算法(Floyd-Warshall)进行分析,发现该算法具有较高的复杂度。鉴于此,结合K-means聚类对Floyd-Warshall算法进行改进。首先利用K-means聚类将物流配送节点以物流配送中心为簇心进行聚类,将物流配送节点进行区域划分,按照起点→起点物流配送中心→终点物流配送中心→终点的顺序,使用Floyd-Warshall算法进行计算得到最佳的配送路径。实验结果表明:使用K-Means聚类可以将物流配送中心的数量按配送节点进行分类;聚类完毕后能够规划出一条最优的物流配送路径;改进后的Floyd-Warshall算法规划的路径更短,规划路径最大相差25公里。
In order to optimize logistics distribution path,improve efficiency and reduce time cost,it was proposed for an optimal path planning model of logistics distribution based on improved Floyd-Warshall algorithm.Through the full analysis of Floyd-Warshall algorithm,it is found that the algorithm has high complexity,so the Floyd-Warshall algorithm is improved by combining K-Means clustering.Firstly,K-Means clustering was used to cluster the logistics distribution nodes with the logistics distribution center as the cluster center,and the logistics distribution nodes were divided into regions.According to the order of starting point→starting point logistics distribution center→ending point logistics distribution center→ending point,Floyd-Warshall algorithm was used to calculate and get the best distribution path.The experimental results show that K-Means clustering can classify the number of logistics distribution centers and distribution nodes.After clustering,an optimal logistics distribution path can be planned;The path planned by the improved Floyd-Warshall algorithm is shorter,and the maximum difference between the planned paths is 25 kilometers.
作者
刘爱萍
LIU Ai-ping(Software College,Quanzhou Institute of Information Engineering,Quanzhou Fujian 362000,China)
出处
《广州航海学院学报》
2025年第3期57-63,共7页
Journal of Guangzhou Maritime University
基金
福建省自然科学基金项目(2023J011800)。
