A novel storage location assignment in multi-pickers picker-to-parts systems integrating scattered storage, demand correlation, and routing adjustment

Abstract

Congestion always occurs in the multi-pickers picker-to-parts picking systems. In this paper, we propose a multi-pickers-based scattered storage location assignment (MPSSLA) strategy. To reduce the probability of congestion and working time of pickers, MPSSLA allows the same stock keeping units (SKUs) to be stored in multiple storage locations. Additionally, it assigns SKUs with high and middle demand correlations to storage locations that are as close as possible to each other. Moreover, a route adjustment method that considers congestion is proposed to adjust the working routes. This further improves the picking efficiency. The working process of pickers in MPSSLA is modelled as a space–time network and an algorithm is designed to determine the optimal solution. Through numerical experiments, the applicability and effectiveness of MPSSLA are analysed considering several main factors. The results show that the proposed algorithm is highly efficient and MPSSLA can achieve better optimisation results than the traditional centralised storage strategy in the multi-pickers picker-to-parts picking system. The proposed storage location assignment strategy can improve the warehouse operation efficiency of the multi-pickers picker-to-parts picking systems with high demand skewness and a large number of pickers.