Order and rack sequencing in a robotic mobile fulfillment system with multiple picking stations

The robotic mobile fulfillment system, where mobile robots carry racks to stationary stations for human pickers, is widely used in e-commerce warehouses. The operational efficiency of the system is largely affected by the organization of the order picking process. In this paper, we investigate an order picking tactic in a robotic mobile fulfillment system that allows racks moving between multiple picking stations in order to feed more orders during one visit and therefore save the overall throughput time. To evaluate this operational tactic's effectiveness, we propose a mathematical model to jointly optimize the order assignment, order sequencing, rack selection, and rack sequencing. A two-stage hybrid heuristic algorithm framework is then presented, including order assignment in the first stage and order and rack sequencing in the second stage. We conduct numerical experiments to validate the proposed algorithms' performance under different strategies and find out that the inter-station operation can significantly save order throughput time on the testing cases. We also investigate the effects of several factors, including the number of picking stations, their capacities, the stock keeping unit diversity, and queue length. Furthermore, a solid simulation is carried out to show the rationale of using rack moves as the objective rather than the completion time.

Automated summary

This paper investigates an order picking tactic in a robotic mobile fulfillment system that allows racks to move between multiple picking stations to process more orders and save time. Numerical experiments show that inter-station operations can significantly reduce order throughput time.