Inventory allocation in robotic mobile fulfillment systems

Abstract

A Robotic Mobile Fulfillment System is a recently developed automated, parts-to-picker material handling system. Robots can move storage shelves, also known as inventory pods, between the storage area and the workstations and can continually reposition them during operations. This article shows how to optimize three key decision variables: (i) the number of pods per SKU; (ii) the ratio of the number of pick stations to replenishment stations; and (iii) the replenishment level per pod. Our results show that throughput performance improves substantially when inventory is spread across multiple pods, when an optimum ratio between the number of pick stations to replenishment stations is achieved and when a pod is replenished before it is completely empty. This article contributes methodologically by introducing a new type of Semi-Open Queueing Network (SOQN): cross-class matching multi-class SOQN, by deriving necessary stability conditions, and by introducing a novel interpretation of the classes.

Keywords:

• Material handling
• mobile fulfillment
• queueing systems
• robotics
• warehousing

Additional information

Notes on contributors

Tim Lamballais Tessensohn

Tim Lamballais Tessensohn has been working as a junior scientist at TNO since 2017, with a focus on operations research and (semi-) autonomous systems. Before coming to TNO, he worked at the Erasmus University Rotterdam as a PhD candidate on the topic of stochastic modeling of material handling systems, specifically robotic mobile fulfillment systems. He graduated cum laude in the master program Econometrics and Management Science with a specialization in operations research and quantitative logistics.

Debjit Roy

Debjit Roy is an associate professor in the production and quantitative methods area at the Indian Institute of Management Ahmedabad. He holds a Ph.D. in industrial engineering and an MS in manufacturing systems engineering from the University of Wisconsin-Madison, USA in addition to an M.Sc. (Engineering) from the Indian Institute of Science, Bangalore, India. He is also a Visiting Professor at the Rotterdam School of Management, Erasmus University where he is associated with the SmartPort and Material Handling Forum initiative. His research focuses on estimating the performance of logistics and service systems such as container terminals, automated distribution centers, vehicle rental, shared transportation, and restaurant systems using stochastic models, optimization, and data-driven simulation. He has published in several leading IEOR and management journals such as Transportation Science, EJOR, IIE Transactions, Journal of Operations Management and Interfaces.

René B.M. De Koster

René (M.) B.M. de Koster is a professor of logistics and operations management at Rotterdam School of Management, Erasmus University, and chairs the department Technology and Operations Management. He holds a Ph.D. from Eindhoven University of Technology (1988). Currently, he holds guest lecturing positions at two other universities and is the 2018 honorary Francqui Professor at Hasselt University. His research interests are warehousing, material handling, and behavioral operations. He is the founder of the Material Handling Forum and is author/editor of books and over 200 papers in books and academic journals. He is associate editor of Transportation Science and Operations Research.