Multi-objective optimization of green aluminum supply chain network design under resource constraints

Aiming to address the imminent issues such as carbon dioxide emissions and water consumption in the supply chain of aluminum production, this study proposes a decision making support framework that consists of three components, namely, the life cycle analysis, the optimization model of green supply chain network, and the multi-objective optimization based on the augmented epsilon-constraint method. The integrated decision making support method is employed for deep analysis of multi-objective optimization problem with multiple resource constraints, by taking into account various technological combination of electricity production, including conventional coal-fired generation, biomass, and photovoltaic (PV) plus electricity storage, as well as the effect of carbon market uncertainty. The results of the case study show that: The economics objective and the objective of water resource saving are contradictory in the model solutions. The choices of suppliers are affected by preference of decision making as well as the uncertainty of carbon price. Under higher stringent constraints of resource, low-carbon generation technologies are more likely opted for, which also leads to the co-benefit of water resource saving. Coal-fired power generation is opted out in all the Pareto solutions under high carbon price, being replaced by the PV plus power storage system. The study demonstrates the effectiveness of the proposed framework in the multi-objective optimization problem of resource supply chain, and provides support for devising the relevant strategies under the multi-faceted constraints of resource and environmental impact. © 2020, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.