Sustainable supply chain network design using products' life cycle in the aluminum industry.

This study provides a three-objective mixed-integer linear mathematical model to design a sustainable closed-loop supply chain network in the aluminum industry. In this regard, the proposed model optimizes economic, social, and environmental objectives simultaneously. The main contribution of this research is to provide a framework for the sustainable aluminum supply chain in Iran by applying the life cycle assessment (LCA) to estimate the environmental impacts and using two novel meta-heuristic algorithms to optimize the proposed mathematical model. In this regard, the multi-objective gray wolf optimizer (MOGWO), the multi-objective red deer algorithm (MORDA), and augmented epsilon constraint (AEC) are used to achieve Pareto optimal solutions. Comparisons between solutions methods show that the MOGWO algorithm and MORDA have a very high advantage over the AEC method in terms of the scatter of Pareto solutions. Moreover, the statistical tests indicate that the MORDA has an advantage over MOGWO in terms of Pareto boundary diversification as well as the quality of solutions. On the other hand, results of the implementation in the aluminum industry show that increasing the coefficient of recycled materials' use in the production of secondary aluminum has a significant impact on the Pareto boundary and leads to reducing production costs and in particular the reduction of carbon dioxide emissions.