A bi-level memetic algorithm for the integrated order and vehicle scheduling in a RMFS

A Robotic Mobile Fulfillment System (RMFS) is a parts-to-picker system designed for e-commerce warehousing where robots are used to fetch inventory pods from the storage area and transport them to the appropriate workstation. At these stations human workers pick the required amount of goods from the pods to fulfill the active orders. The RMFS is composed of several hard sub-problems which are typically solved sequentially. To the best of the authors’ knowledge, there exists no algorithm that integrates multiple of these problems and consider the interdependencies between them. This paper focuses on solving the integrated order to workstation and robot scheduling problem and proposes a bi-level memetic algorithm. Computational experiments on a wide range of problem instances show the importance of considering an integrated solution approach over a sequential approach for this complex problem. The experiment clearly show the impact of the existing interdependencies. Moreover, the study shows that the pod selection problem for the order fulfillment has a significant impact on the overall system performance. The inventory pod’s consolidation opportunity and distance from the picking station has to be taken into account. • An integrated solution approach for the Robotic Mobile Fulfillment System. • A flexible bi-level memetic algorithmic framework. • Scheduling and routing of Automated Guided Vehicles in complex systems. • New problem instances for the Robotic Mobile Fulfillment System.