Abstract

Purpose – The purpose of this paper is to develop a mathematical model for the design of a multi-stage reverse supply chain. Design/methodology/approach – A mixed-integer linear programming formulation is used to model the network. Different data sets are generated randomly. Lingo, an optimisation package is used to solve the model developed. Findings – The model is able to provide optimum solutions regarding the number and location of different facilities to be established in the network. The flow of different items through the network is also obtained. Analysis of the results shows the sensitivity of design decisions with respect to the changes in the input parameter value. Research limitations/implications – The authors consider only a single-product and single-period situation for this study. Further research can be done by considering a multi-product and multi-period situation. Uncertainty in data can also be included for future research. Practical implications – The developed model can aid the managers in taking optimum decisions regarding the network design of a reverse supply chain. The analysis of the model for the variations in the input parameter values can also help the decision makers to take better decisions in a reverse supply chain. Originality/value – The present research simultaneously considers two types of product return, namely, end-of-life and end-of-use product return, in a seven stage supply chain. Different recovery options such as recycling and remanufacturing are also incorporated into the model.

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