To facilitate more efficient and environmentally-friendly order picking operations, this study explores the optimal storage assignment policy in the Kiva mobile fulfilment system. First, temporal association analysis and a clustering approach are employed to identify highly correlated items to be stored in the same rack. Next, in order to avoid AGV blocking, a new turnover-rate-based decentralized storage policy (TRBDSP) is proposed. Subsequently, an order picking performance evaluation method is presented. Finally, simulation studies are performed to ascertain the effectiveness of TRBDSP. The results show that the new approach can significantly improve order picking efficiency and reduce AGV energy consumption.

为了促进更高效和环保的订单拣选操作，本研究探索了Kiva移动履行系统中的最佳存储分配策略。首先，采用时间关联分析和聚类方法来识别要存储在同一机架中的高度相关的项目。接下来，为了避免AGV阻塞，提出了一种新的基于周转率的分散存储策略（TRBDSP）。随后，提出了一种订单拣选性能评估方法。最后，进行仿真研究以确定TRBDSP的有效性。结果表明，该新方法可以显着提高订单拣选效率并减少AGV能耗。