Optimizing electric vehicle battery recycling system for sustainability, resilience, and responsiveness: A South Korean case study

The global rise in electric vehicle (EV) adoption has led to a sharp increase in decommissioned EV batteries (EVBs), making EVB recycling a major challenge under environmental and resource constraints. Despite this growing need, prior studies largely emphasize cost efficiency or sustainability while giving limited attention to downstream resilience and responsiveness. To address this gap, this study proposes the decommissioned electric vehicle battery recycling supply chain (DEVB-RSC) model, a multi-objective optimization framework integrating sustainability, resilience, and responsiveness. The framework combines fuzzy programming to handle parameter uncertainty with support vector regression (SVR) to forecast discarded EVB volumes for proactive planning. The model is validated through a South Korean case study. SVR achieves regional forecasting errors between 2.04% and 8.44% MAPE, supporting reliable estimation of EVB supply. Under the balanced multi-objective solution, the DEVB-RSC model attains 60.0%, 58.1%, 58.1%, 71.4%, and 58.1% achievement levels for the cost, environmental, social, non-resilience, and responsiveness objectives, indicating that the framework can sustain balanced performance across competing dimensions. The results also show that cost, GHG emissions, and non-resilience objectives are broadly aligned, but still lead to different strategic decisions regarding facility location, capacity, and recycling technology. In addition, a 10% increase in recovered material and second-life revenues raises NPV by approximately 60% over the baseline scenario, while IRR increases from 9.48% to 14.15%, which highlights the importance of downstream value recovery for economic feasibility. The study offers useful insights for policymakers, EV manufacturers, and other stakeholders involved in designing sustainable and resilient EVB supply chains.