The buffer allocation problem in production lines: Formulations, solution methods, and instances

Abstract

Flow production lines with finite buffer capacities are used in practice for mass production, e.g., in the automotive and food industries. The decision regarding the allocation of buffer capacities to mitigate throughput losses from stochastic processing times and unreliable stations is known as the Buffer Allocation Problem (BAP).

 This article classifies and reviews the literature on the BAP with respect to different versions of the optimization problem. It considers the detailed characteristics of the flow lines, the objective function, and the constraints. Moreover, a new classification scheme for solution methods is presented that differentiates between explicit solutions, integrated optimization methods, and iterative optimization methods. The characteristics of test instances derived from realistic cases and test instances used in multiple references are discussed.

 The review reveals gaps in the literature regarding the considered optimization problems and solution methods, especially with a view on realistic lines. In addition, a library, FlowLineLib, of realistic and already used test instances is provided.

KEYWORDS:

• Buffer allocation problem
• flow production line
• classification
• survey
• instances
• FlowLineLib

Acknowledgements

The authors are grateful to the anonymous referees for helpful suggestions that improved the presentation of the article.

Additional information

Funding

This research was in part supported by the Julius Paul Stiegler Memorial Foundation.

Notes on contributors

Sophie Weiss

Sophie Weiss received her diploma in Business Mathematics from the University of Cologne in 2010. She has been a visiting scholar at Shanghai Jiao Tong University and was awarded a Ph.D. from the University of Mannheim in 2015. Her main research interest is in the analysis and optimization of manufacturing systems.

Justus Arne Schwarz

Justus Arne Schwarz graduated with a diploma in industrial engineering from the Karlsruhe Institute of Technology and an M.S. in engineering and technology management from Portland State University. He received a Ph.D. from the University of Mannheim in 2016. Since then he has been a visiting scholar at the Massachusetts Institute of Technology and Koc University. He is currently an assistant professor in the area of operations management at the Business School of the University of Mannheim. He conducts research on performance evaluation and design of dynamic and stochastic production systems.

Raik Stolletz

Raik Stolletz studied mathematics, computer science, and business administration at the Technical University of Berlin. He received a Ph.D. from the Technical University of Clausthal in 2002 and the degree of Habilitation from the Leibnitz University of Hannover in 2009. In 2009–2010 he was an associate professor at the Technical University of Denmark. He currently is a full professor of production management at the Business School of the University of Mannheim. His research projects focus on quantitative decision support in the design and management of manufacturing and service systems. He has published articles in journals such as European Journal of Operational Research, Manufacturing & Service Operations Management, OR Spectrum, and Production and Operations Management.