Designing a Robust Post-Sales Reverse Logistics Network

Abstract

The concept of green supply chain management has attracted many academics and professionals due to various reasons such as governmental regulations, customers’ awareness, and economic benefits of greening supply chains. One of the first and important decisions for greening a supply chain is to design supply chain networks while considering environmental factors. In this study, a multiproduct post-sales reverse logistics network operated by a third party logistics service provider is considered, which consists of collection centers, repair facilities, production plants, and disposal centers. It is assumed that amount of products returns from customers are uncertain parameters varying in intervals with known nominal and shift values. A bi-objective robust mixed integer linear programming model is presented for minimizing network design costs as well as minimizing total weighted tardiness of returning products to collection centers. Various decisions including location of repair facilities, allocation of repair equipments to facilities, and material flows are simultaneously considered. The proposed robust model incorporates the uncertainty budget concept, which could represent the decision-maker’s degree of risk-awareness. At the end, a numerical example demonstrates the ε-constraint method success in obtaining a list of Pareto-optimal solutions for the proposed robust model.