Application of Particle Swarm Optimization based on Clustering Analysis in Logistics Distribution

摘要：

In order to solve the modern logistics problem of vehicle distribution, a particle swarm optimization (PSO) algorithm based on clustering analysis is proposed in this paper. This algorithm clusters the target points in need of distribution primarily by DBSCAN algorithm, and then weighted k-means algorithm is used to cluster the target points finally based on the primary clustering. Corresponding vehicles are allocated to every target cluster according to result of clustering analysis, furthermore, path of vehicles are optimized by use of PSO algorithm until all the distribution tasks are finished. Simulation experiments result shows that PSO algorithm based on clustering analysis is feasible and effective in modern logistics distribution process.

关键词： logistics distribution particle swarm optimization (PSO) algorithm DBSCAN algorithm weighted k-means algorithm

作者: Haobin Shi Zhonghua Li Wenbin Li Zhujun Yu

作者单位: School of Computer Science Northwestern Polytechnical University Xian, China School of Information Technology Jiangxi University of Finance & Economics Nanchang, China

会议类型: 国际会议

会议名称: 2009 International Conference on Management of e-Commerce and e-Government ICMeCG 2009(第三届电子商务与电子政务管理国际会议)

会议地点: 南昌

会议语种:英文

页码: 291-295

在线出版日期: 2009-09-01（万方平台首次上网日期，不代表论文的发表时间）