Research on Multi-objective clustering Optimization of Logistics Distribution Line in E-commerce Environment

Shiming Liu¹, Huihong Chen^2*

1School of Management, Guangzhou Panyu Polytechnic University, Guangzhou, 511483,  China

2School of Information Engineering, Guangzhou Panyu Polytechnic University, Guangzhou, 511483, China

Abstract: In order to improve the ability of logistics distribution line optimization, a multi-objective clustering algorithm based on particle cluster is proposed. The maximum density sparsity detection of logistics lines and adaptive optimization method are used to schedule logistics distribution routes, and the selection model of logistics distribution routes under e-commerce environment is constructed. Particle swarm optimization (PSO) algorithm is used to construct the multi-objective optimization model of logistics distribution line in e-commerce environment, and the global optimization characteristic of particle swarm optimization algorithm is used to optimize the logistics distribution route. The attribute of multi-objective sample set of logistics distri-bution line is standardized, the shortest optimization value of logistics distribution line is solved, and the mul-ti-objective clustering is carried out according to the result of optimization solution. The particle swarm adap-tive clustering method is used to realize the multi-objective optimal selection of logistics distribution routes. The simulation results show that this method has better performance in optimizing control of logistics distri-bution lines, the efficiency of logistics is improved, the loss of logistics lines is reduced, and it can improve the throughput performance of logistics lines.

Keywords: E-commerce; Logistics; Distribution routes; Multi-objective clustering; Scheduling