ABSTRACT

With the advancement of AI and the widespread application of IoT and cloud computing, the pick-and-pass system (PKPS) can potentially be transformed into a cyber-physical system (CPS) based intelligent warehouse picking system. This paper proposes a CPS-based PKPS with a heuristic multi-objective genetic algorithm to solve the NP-hard storage assignment problem (SAP) for order picking operations in an e-commerce-based warehouse. The proposed algorithm considers both the workload balance between picking lines and emergency replenishment during picking operation. Finally, the study shows that the proposed algorithm is effective in improving the efficiency of picking operations based on software simulation.

摘要

随着人工智能的进步以及物联网和云计算的广泛应用，拣配系统（PKPS）有可能转变为基于信息物理系统（CPS）的智能仓库拣选系统。本文提出了一种基于 CPS 的 PKPS，采用启发式多目标遗传算法来解决基于电子商务的仓库中订单拣选操作的 NP 难存储分配问题 (SAP)。所提出的算法考虑了拣货作业期间拣货线和紧急补货之间的工作负载平衡。最后，研究表明，所提出的算法能够有效地提高基于软件仿真的拣货作业效率。