An efficient multi-agent approach to order picking and robot scheduling in a robotic mobile fulfillment system

Abstract

This paper presents a Multi-Agent System (MAS) for optimizing the scheduling and routing of mobile robots and human pickers in a Robotic Mobile Fulfillment System (RMFS). The RMFS is a system designed for e-commerce warehousing where autonomous mobile robots are used to fetch inventory pods, also referred to as racks, from the storage area and transport them to the appropriate picking station where human pickers pick the required number of goods. The system requires the solution of several hard decision problems like: the order-to-picking station assignment and sequencing, the pod selection, and the multi-robot task allocation. The proposed solution approach employs decentralized scheduling mechanisms, i.e. auctions and dispatching rules, to communicate and distribute picking and retrieval tasks among the agents. Various dispatching rules are identified and analyzed over a wide set of problem instances of the RMFS with varying numbers of mobile robots, picking stations, and order sizes. The proposed MAS framework shows promising results and requires only a fraction of the computation time compared to a centralized scheduling algorithm. The MAS also includes both unidirectional and bidirectional lanes. Although additional complexity in collision avoidance is introduced when using bidirectional lanes, it allows for better system performance.