Location, inventory and testing decisions in closed-loop supply chains: A multimedia company

Abstract

Our partnering firm is a Chinese manufacturer of multimedia products that needs guidance developing its imminent Closed-Loop Supply Chain (CLSC). To study this problem, we take into account location, inventory, and testing decisions in a CLSC setting with stochastic demands of new and time-sensitive returned products. Our analysis pays particular attention to the different roles assigned to the reverse Distribution Centers (DCs) and how each option affects the optimal CLSC design. The roles considered are collection and consolidation, additional testing tasks, and direct shipments with no reverse DCs. The problem concerning our partnering firm is formulated as a scenario-based chance-constrained mixed-integer program and it is reformulated to a conic quadratic mixed-integer program that can be solved efficiently via commercial optimization packages. The completeness of the model proposed allows us to develop a decision support tool for the firm and to offer several useful managerial insights. These insights are inferred from our computational experiments using data from the Chinese firm and a second data set based on the U.S. geography. Particularly interesting insights are related to how changes in the reverse flows can impact the forward supply chain and the inventory dynamics concerning the joint DCs.

KEYWORDS:

• Closed-loop supply chain
• conic quadratic mixed-integer program
• role of reverse DCs
• Chinese manufacturer

Acknowledgements

We would like to thank the anonymous reviewers for their suggestions that helped to improve this article.

Funding

This research is partially supported by the National Natural Science Foundation of China under grants 71771135, 71371106 and 71332005.

Additional information

Notes on contributors

Zhi-Hai Zhang

Zhi-Hai Zhang is an associate professor in the Industrial Engineering Department at Tsinghua University. He received his B.S and Ph.D. in mechanical engineering from Tsinghua University in 1997 and 2002, respectively. His current research interests focus on production and operational management, resource allocation optimization, supply chain and logistics management, production planning and scheduling, large-scale optimization. He has published numerous articles in journals such as Transportation Science, IISE Transactions, Transportation Research Part B, European Journal of Operational Research, Omega, Computer and Operations Research, etc.

Gemma Berenguer

Gemma Berenguer is an assistant professor at the Krannert School of Management, Purdue University. She received her Ph.D. in operations research at the University of California, Berkeley. She also holds an M.Eng.in logistics and supply chain management, an M.S. in economics, and a B.S. in mathematics. Professor Berenguer's major research topics are related to supply chain design, sustainable operations and nonprofit supply chain management. She has experience collaborating with private, public and nonprofit organizations in the consumer goods, transportation, electronic goods, global healthcare, and solar energy sectors. She has published in journals such as Operations Research, Production and Operations Management, Transportation Science and Journal of Operations Management.

Xiaoyong Pan

Xiaoyong Pan is the general manager of China Sichuan Changhong Intelligent Manufacturing Technology Co. Ltd. He worked as a postdoc at Tsinghua University from 2004 to 2006. His current work focuses mainly on intelligent and green manufacturing.