Title: An improving clustering algorithm for order batching of e-commerce warehouse system based on logistics robots

Authors: Fei Xue; Tingting Dong; Zixiang Qi

Addresses: School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Economics, Beijing Wuzi University, Beijing 101149, China

Abstract: In this paper, the batching model and strategy of orders in e-commerce warehouse system based on logistics robots are studied. First, different order picking patterns are put forward by analysing the operation process of logistic robots in the e-commerce warehouse system. Then the order batching model is established based on two objectives of the minimisation of the total picking and traveling time of logistics robots and the minimisation of the longest picking time used among all picking stations. The model is solved using the improved clustering algorithm. Finally, the results show that the picking pattern of batching first and combining last has the advantages of higher put-out-storage efficiency by simulating experiment and the comparison analysis of order picking efficiency corresponding to different order picking patterns.

Keywords: logistics robots; e-commerce warehouse system; order batching; clustering algorithm.

DOI: 10.1504/IJWMC.2018.094633

International Journal of Wireless and Mobile Computing, 2018 Vol.15 No.1, pp.10 - 15

Available online: 03 Sep 2018 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article