Order batching and batch sequencing in an AMR-assisted picker-to-parts system

Abstract

Efficient order fulfillment processes in warehouses are a key success factor in times of increasing global retail sales volumes and same-day deliveries. To streamline order fulfillment processes, warehouse managers frequently rely on autonomous mobile robots (AMRs). By supporting human order pickers with AMRs, unproductive picker walking time can be reduced, which is essential for increasing the performance of a traditional picker-to-parts system. We study an AMR-assisted picker-to-parts system in which the warehouse is partitioned into disjoint zones, each with one order picker assigned to it. A set of customer orders is given, each associated with a due date until which its items are to be collected. Each AMR of a given fleet is responsible for transporting the items of a single batch of customer orders from the picking area to the depot. An order picker collects those batch items that are stored in her zone and transports them to a handover location. The AMR visits the handover locations and returns to the depot after collecting all batch items. The objective is to minimize the total tardiness of all customer orders. We define the resulting problem as mixed integer program and provide an efficient heuristic solution approach. Furthermore, we investigate the influence of increasing the AMR fleet size and varying travel and walking speed ratios between AMRs and order pickers. We find that a slight increase in the speed ratio leads to a larger reduction of the total tardiness compared to increasing the AMR fleet size.