Optimizing picking operation in an omnichannel warehouse using simulation and automation techniques

Abstract

Omnichannel retailing involves the integration of brick-and-mortar stores and online platforms, which can provide a seamless shopping experience to consumers. However, proper functions and features provided by retail alone may not suffice. Therefore, it is imperative to consider the role of the omnichannel warehouse, which offers significant features such as shorter lead time, lower cost, and larger product assortments. Our research focuses on picking operations as it is one of the primary operations in the omnichannel warehouse that consumes a high amount of time, labor, and cost. We aim to enhance the efficiency of picking operations in an omnichannel warehouse through the utilization of simulation and automation methodologies. Flexsim software was selected as the simulation tool after a thorough analysis of available methodologies. We use three modern automated technologies, conveyor belts, mobile robotic fulfillment systems, and automated guided vehicles, and identify the most appropriate picking technique for the omnichannel warehouse through a comparison of simulation models. Finally, we develop a basic framework utilizing operators for executing pickup operations and generating multiple models, incorporating automated techniques. Subsequently, a comparative analysis of all models is conducted based on each scenario’s time, distance, and cost to identify the most optimal scenario. To implement the OC concept in future studies, it should include new picking methods, operations, and sectors.