152 / 2024-04-22 10:40:22

Human-Centric Order Batching and Allocation When Picking With Robot Teammates in the Warehouse

Order picking system,human-centric warehouse management,order batching,order allocation,human-machine collaboration

More e-commerce warehouses deploy automated guided vehicles (AGVs) to assist human pickers in order picking. When picking with robot teammates, not only do human pickers struggle to keep up with the robots, but they also suffer from physical and psychological problems. For example, non-ergonomic injuries from frequent rack visits and stress caused by the unbalanced allocation of picking tasks significantly affect order picking efficiency and the human picker’s state. Unlike the previous studies, we address these problems from a human-centric perspective. We formulate order batching and order allocation optimization models in one go and propose heuristics algorithms to solve them. The results show that our proposed order batching optimization reduces the frequency of human pickers visiting the racks by at least 3.5% at 1,000 order size, which helps avoid potential non-ergonomic injuries in the warehouse. At the same time, our proposed order allocation optimization achieves a balanced and fairly allocation of orders among the human pickers, which alleviates the discomfort of human pickers when picking with robot teammates. Our results also validate the effectiveness of the proposed algorithms. This study makes theoretical and practical contributions to human-machine collaboration in order picking and human-centric warehouse management in the Industry 5.0 era.