A two-stage stochastic model for sustainable and resilient closed-loop supply chain of electric vehicle batteries

To address the growing need for recycling retired electric vehicle (EV) batteries, it is crucial to design a sustainable closed-loop supply chain (CLSC). Meanwhile, the EV battery SC remains vulnerable in today's volatile environment, highlighting the need for resilient designs to mitigate risks. Thus, this study contributes to develop a progressive three-tier modeling framework that evolves from a deterministic “risk-free” model to a stochastic “risk-inclusive” model, and ultimately to a resilient “risk-responsive” model. The model promotes industrial sustainability across economic, environmental, and social dimensions, and introduces five sector-specific resilience strategies to mitigate risks. A scenario-based two-stage stochastic programming approach is employed to address uncertainties in supply, demand, and recycling. The model's effectiveness is validated through a real-world case study of CATL, the world's largest EV battery manufacturer. Results show that the CLSC significantly enhances sustainability compared to one-way SCs. The resilient model improves resilience and reduces costs relative to non-resilient alternatives. The bi-objective model, balancing resilience enhancement and cost reduction, achieves substantial resilience gains with minimal cost increases. The study further demonstrates that comprehensive strategies are more effective than single-focused ones in cost control and resilience enhancement, and that optimal resilience strategies vary significantly with risk types and intensities. Finally, managerial and policy insights are provided based on the findings of the case study and sensitivity analysis.