Production planning and inventory control for a two-product recovery system

Abstract

The significance of product recovery through remanufacturing has been widely recognized and has compelled manufacturers to incorporate product recovery activities into normal manufacturing processes. Consequently, increasing attention has been paid to production and inventory management of the product recovery system where demand is satisfied through either manufacturing brand-new products or remanufacturing returned products into new ones. In this work, we investigate a recovery system with two product types and two return flows. A periodic-review inventory problem is addressed in the two-product recovery system and an approximate dynamic programming approach is proposed to obtain production and recovery decisions. A single-period problem is first solved and the optimal solution is characterized by a multilevel threshold policy. For the multi-period problem, we show that the threshold levels of each period are solely dependent on the gradients of the cost-to-go function at points of interest after approximation. The gradients are estimated by an infinitesimal perturbation analysis–based method and a backward induction approach is then applied to derive the threshold levels of each period. Numerical experiments are conducted under different scenarios and the threshold policy is shown to outperform two other heuristic policies.

Keywords:

• Two-product recovery system
• product returns
• remanufacturing
• multilevel threshold policy
• approximate dynamic programming

Additional information

Notes on contributors

Jie Pan

Jie Pan received his B.Eng. and M.Eng. degrees from Beihang University, China, in 1999 and 2002, respectively. He received his Ph.D. in Industrial and Systems Engineering at the National University of Singapore in 2011. He joined for Integrated Decision Systems Consultancy Pte Ltd (Singapore) as Senior Optimization Consultant in 2013. Prior to this, he worked as a Business Optimization Analyst for Alexandra Health Pte Ltd (Singapore) between 2010 and 2013. He also worked as a research engineer in the School of Information Systems at Singapore Management University in 2009. His research interests include operations research, logistics and supply chain management, forecasting, sales analytics, and inventory optimization.

Yi Tao

Yi Tao is currently an Assistant Professor in the School of Management at Guang Dong University of Technology, China. He received his B.S. (Computer Science) degree from the Beihang University, China, in 2005 and his Ph.D. from Sun Yat-Sen University, China, in 2010. His research interests include logistics and supply chain management, port operations and maritime transportation, and optimization.

Loo Hay Lee

Loo Hay Lee is an Associate Professor in the Department of Industrial and Systems Engineering at the National University of Singapore. He received his B.S. (Electrical Engineering) degree from the National Taiwan University in 1992 and his S.M. and Ph.D. degrees in 1994 and 1997 from Harvard University. His research focuses on the simulation-based optimization, maritime logistics, which includes port operations, and modeling and analysis of logistics and supply chain systems.

Ek Peng Chew

Ek Peng Chew is currently an Associate Professor and Deputy Head (Undergraduate Studies) in the Department of Industrial and Systems Engineering at the National University of Singapore. He received his Ph.D. in Industrial Engineering from the Georgia Institute of Technology. His current research interests include port logistics and maritime transportation, simulation optimization, and inventory management.