Saeedi, MehranParhazeh, SinaTavakkoli-Moghaddam, RezaKhalili-Fard, Alireza2024-05-192024-05-1920240360-83521879-0550https://doi.org10.1016/j.cie.2024.110036https://hdl.handle.net/20.500.12713/5612Transportation is a fundamental requirement of modern life. Vehicles powered by fossil fuels are highly polluting. This study develops a two-stage stochastic programming model to establish a sustainable closed-loop supply chain for Electric Vehicle (EV) batteries. The model considers economic, environmental, and social criteria, including cost, energy consumption, carbon emissions, and job creation. The epsilon-constraint method and three multi-objective meta-heuristic algorithms are utilized to solve problems. Implementing this model in a case study of an EV battery supply chain aids managerial decision-making for optimal center establishment, flow determination, and inventory setting. Finally, essential parameters are analyzed, and several important managerial insights are prepared. The results suggest that investing in used battery collection significantly reduces costs and carbon emissions.eninfo:eu-repo/semantics/closedAccessSustainable Closed -Loop Supply ChainElectric Vehicle BatteryMulti -Objective OptimizationMeta -Heuristic AlgorithmsTwo -Stage Stochastic ProgrammingArticle190WOS:0012030479000012-s2.0-85186769711N/A10.1016/j.cie.2024.110036Q1