Reference Hub8
Design of Closed Loop Supply Chain Networks

Design of Closed Loop Supply Chain Networks

Subramanian Pazhani, A. Ravi Ravindran
Copyright: © 2014 |Volume: 1 |Issue: 1 |Pages: 24
ISSN: 2334-4547|EISSN: 2334-4555|EISBN13: 9781466661868|DOI: 10.4018/ijban.2014010104
Cite Article Cite Article

MLA

Pazhani, Subramanian, and A. Ravi Ravindran. "Design of Closed Loop Supply Chain Networks." IJBAN vol.1, no.1 2014: pp.43-66. http://doi.org/10.4018/ijban.2014010104

APA

Pazhani, S. & Ravindran, A. R. (2014). Design of Closed Loop Supply Chain Networks. International Journal of Business Analytics (IJBAN), 1(1), 43-66. http://doi.org/10.4018/ijban.2014010104

Chicago

Pazhani, Subramanian, and A. Ravi Ravindran. "Design of Closed Loop Supply Chain Networks," International Journal of Business Analytics (IJBAN) 1, no.1: 43-66. http://doi.org/10.4018/ijban.2014010104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Given the importance of operating and managing forward and reverse supply chains in an integrated manner, this article considers an integrated four-stage supply chain network with forward and reverse product flows. We consider a closed loop supply chain (CLSC) network with primarily commercial returns, which could be potentially recovered by light repair operations or by refurbishing. The annual estimate of commercial returns in the United States is in excess of $100 billion. This paper discusses the optimal design of a CLSC network.A mixed integer linear programming (MILP) model is developed to determine the optimal locations of the facilities and the distribution of flows between facilities in the CLSC to maximize the total profit. The model is illustrated using a realistic example applicable to the electronics industries. Even though recycling and refurbishing add cost, the overall supply chain profit increases due to a reduction in the raw material cost. Sensitivity analysis is carried out to determine the effect of return percentage and varying demands of customers who are willing to buy refurbished products. The analysis show that the total supply chain profit increases with the increase in refurbishing activity. Finally, changes in the network design with respect to the uncertainty in these return parameters are also studied. The results show that the changes in return parameters lead to changes in optimal network design implying the need to explicitly consider the uncertainty in these return parameters.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.