A multi-objective optimization approach for green and resilient supply chain network design: A real-life case study

Abstract

This study presents a robust multi-objective optimization model to configure a green global supply chain network structure under disruption. The proposed model is adapted to a global medical device manufacturing system. Economic and environmental issues are considered in designing the network, and mitigation strategies are employed to obtain a resilient supply chain network. To deal with the computational tractability of this non-linear and multi-objective optimization problem, a novel hybrid heuristic is developed that incorporates improved strength Pareto evolutionary algorithm 2 (SPEA2). Computational results indicate that the proposed global supply chain network configuration can respond to its global customers’ demand in agile as well as green manner. Based on our results, the importance of the SC agility is highlighted by increasing the budget of uncertainty, and some of well-known mitigation strategies are in contradiction to the agile production paradigm.