Analytical models for warehouse configuration

Abstract

The performance of a warehouse is impacted by how it is configured, yet there is no optimization model in the literature to answer the question of how to best configure the warehouse in terms of warehouse shape and the configuration of the dock doors. Moreover, the building blocks for such a model (put-away, replenishment, and order picking models that can be combined in an optimization model) are either not available (in the case of replenishment) or built on a set of inconsistent assumptions (in the case of put-away and order picking). Therefore, this article lays the foundation for more sophisticated warehouse configuration optimization models by developing the first analytical model for replenishment operation performance and extending put-away and order picking performance models. These new models are used to address a question motivated by industry: the optimal configuration of a case-picking warehouse in terms of the shape of the facility and whether the facility is configured with dock doors on one or both sides. An example is presented to demonstrate the use of the proposed models in answering such a question, quantifying the benefit of using an integrated approach to warehouse configuration.

Keywords:

• Warehouse shape
• warehouse design
• put-away
• order picking
• replenishment
• random storage
• class-based storage

Additional information

Notes on contributors

Lisa M. Thomas

Lisa M. Thomas is now a Research Associate with Fortna, Inc. She graduated from the University of Arkansas in August 2013 with a Ph.D. in Industrial Engineering. She received a B.S. in Computer Systems Engineering and an M.S. in Industrial Engineering from the University of Arkansas. As a doctoral student, she worked with Professor Russell D. Meller on research in the area of overall warehouse design. The contents of this article are based on a portion of her dissertation research. Her dissertation research resulted in two best paper awards in the Facility Logistics track of the Industrial & Systems Engineering Research Conference. She is a member of Alpha Pi Mu and IIE.

Russell D. Meller

Russell D. Meller holds the title of the Hefley Professor of Logistics and Entrepreneurship at the University of Arkansas. He joined the Department of Industrial Engineering as Director of the Center for Excellence in Logistics and Distribution (CELDi; a National Science Foundation Industry/University Cooperative Research Center) in 2005 after 6 years on the faculty at Virginia Tech, where he most recently held the title of Professor of Industrial & Systems Engineering in the Grado Department of Industrial & Systems Engineering. He joined Virginia Tech after 7 years on the faculty at Auburn University. He received his B.S.E., M.S.E., and Ph.D. in Industrial and Operations Engineering from the University of Michigan. In 1996 he received a CAREER Development Grant from the National Science Foundation. In 2002 he received the Outstanding Young IE award from the Institute of Industrial Engineers (IIE). In 2011 he was awarded the Technical Innovation in Industrial Engineering Award from IIE and the Reed-Apple Award from the Material Handling Education Foundation. In 2011 he won the David F. Baker Distinguished Research Award from IIE. His research interests lie in facility logistics, in particular, warehouse design, facilities layout and location, and automated material handling systems. He co-authored papers that won the 2003–2004 and 2008–2009 Best Paper Awards for IIE Transactions on Design & Manufacturing. In addition, he is a Department Editor for IIE Transactions. He is a member of Alpha Pi Mu, a Past President of the College-Industry Council on Material Handling Education, and a Fellow of the IIE.