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

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.