Finding the right one: Decision support for selecting cost-efficient order picking solutions

Abstract

Enabled via recent technological advances coupled with the advent of new systems providers and decreased price points, automated and robotized order-picking solutions (e.g., pick-assisting autonomous mobile robots) have evolved as a surging market. Such innovative picking technologies aim to reduce labor costs, use available space more efficiently, and increase throughput rates. As implementation projects and the variety of solutions rise, managers decide which ones to select for their specific warehouse and products. However, comprehensive decision models for this strategic problem are lacking in the pertinent literature. We propose a mathematical optimization model for the novel problem that selects and sizes order-picking solutions and assigns them products and warehouse spaces. Expert interviews are used to identify the comprehensive decision-relevant costs and constraints. Specifically, we minimize setup, module, labor, and error costs while adhering to characteristics related to the area (e.g., available space), technology (e.g., throughput, handling capabilities of certain products), and product (e.g., physical dimensions). We conduct a case study and complement our findings with numerical experiments. We find significant cost reduction potential of up to 57% by selecting a mix of different order-picking solutions. Further analyses highlight the need to retain human workers and to account for maximum labor capacity.

Keywords:

• Automated warehouse
• smart warehouse
• order picking system
• robotic systems
• flexible automation
• warehouse design
• decision support
• facilities planning
• distribution center
• material handling equipment

Additional information

Notes on contributors

Fabian Schäfer

Dr. Fabian Schäfer is a postdoc at the Department of Supply Chain and Value Management at the Technical University of Munich (TUM) in Germany. He holds a PhD in Business Administration. His research focuses on focuses on decision support systems. One of the papers, “Maximizing Profit via Assortment and Shelf-Space Optimization for Two-Dimensional Shelves,” he has worked on has been published by the Production and Operations Management (POM) Journal.

Fabian Lorson

Fabian Lorson, MSc, is a research associate and doctoral student at the Chair of Supply and Value Chain Management at the Technical University Munich (TUM), Germany. He holds a double Master’s degree (MSc) in Business Administration/Supply Chain Management from the University of Cologne and the CEMS Alliance. Before his doctorate, he worked as a consultant for one of the top management consultancies. He advised industrial clients on warehousing and distribution efforts. Fabian Lorson currently works on several collaborations of the TUM with leading retailers and warehouse system providers. Fabian focuses on warehouse automation and the behavioral implications of human-machine interactions with novel automated and robotized warehousing systems in his research. His latest research has been published in IISE Transactions.

Alexander Hübner

Prof. Dr. Alexander Hübner is a tenured Full Professor for Supply and Value Chain Management at the Technical University Munich (TUM) in Germany. Prof. Hübner holds a PhD (2011) and a Diploma in Business Administration from the Catholic University of Eichstätt-Ingolstadt, where he also completed his Assistant Professorship. He then moved to the Massachusetts Institute of Technology (MIT), where he was an Associate Professor for Logistics and Supply Chain Management at the Luxembourg Centre of Logistics. Before joining the TUM, he headed the Institute for Supply Chain Management at the European Business School in Oestrich-Winkel. He also worked as a Project Manager with a top management consultancy serving retail and consumer goods clients (2005-2012). His research was funded by the German Ministry of Research and by the German Academic Exchange Service. His latest research has been published, amongst others, in IISE Transactions, Production, and Operations Management, European Journal of Operational Research, Transportation Science, Omega. His research focuses on decision support systems in logistics and the retail industry. He founded and led the EURO Working Group “Retail Operations.” He served as guest Editor for the Journal of Operations Management, EJOR, and OR Spectrum on special issues related to retail operations. He is the Editor-in-Chief of Logistics Research.