Simulation Model for a Semi-automated Retail Order Picking System Under Uncertainty

Abstract

Due to the growth of e-commerce, retail order picking problems are nowadays one of the most challengeable issues in logistics networks. Conventionally, semi-automated picking systems are implemented, using a conveyor for transportation and operators for preparation. Customer demand being volatile, the sustainability of the system relies on digitalization and reconfigurability, regarding both the physical and information system. From an operational standpoint, the performance is driven by scheduling approaches to manage the bins' flow however the system is prone to uncertainty. We develop a decision tool based on a simulation model to accurately reflect the real-life situation and the human-conveyor interaction. Our aim is to evaluate the practical flow of the system with uncertain preparation times compared to a theoretical schedule obtained by a deterministic optimization approach. Numerical experiments including an industrial case study are presented and discussed.