关键词: 关键词：路径规划, 聚类分析, 数据分割, k条最短路径, K-means算法, 粒子群算法

Abstract: Abstract: In Large-scale logistics center ， if logistics management information system can be used normally， it is necessary to study the problem of vehicle routing in multi-distribution centers.We want to use as few vehicles as possible to complete the delivery of goods and minimize the total mileage.K-shortest paths in multi-center path planning has conducted in-depth research， the multi-path planning problem has been realized by using the traditional clustering algorithm.However， in the real multi-distribution-center vehicle routing planning， there are specific restrictions on the transportation capacity of transportation vehicles and the needs of users. We introduce constraint mechanism on the clustering algorithm to reduce the dimension of multi distribution center problem to single distribution center problem by clustering algorithm， and particle swarm optimization is introduced to solve the optimal solution of multi-path planning for single distribution center.The experiment proves the superiority of this method：the practice proves that the convergence speed of this method is at least n （number of distribution centers) times faster than that of the traditional particle swarm optimization algorithm， which provides a new solution for path planning.

Key words: Key words: path planning, cluster analysis, data segmentation, K-shortest paths, K-means algorithm, particle swarm optimization