Sustainable reverse logistics network design for end-of-life electric vehicle batteries under uncertainty: a fuzzy chance-constrained multi-objective approach for Saudi Arabia

Introduction The rapid expansion of electric vehicle (EV) adoption in Saudi Arabia under Vision 2030 generates an urgent need for end-of-life (EoL) power battery management infrastructure. Despite ambitious circular economy targets, the Kingdom currently lacks a standardized recycling network, and no quantitative optimization framework exists for the Gulf region's specific regulatory and market context. Methods This paper proposes a fuzzy chance-constrained multi-objective mixed-integer nonlinear programming (MO-MINLP) model for the optimal design of a three-tier EV battery reverse logistics network, simultaneously minimizing economic costs and environmental carbon emission costs under uncertain battery State of Health (SoH) distributions and fluctuating market prices. Uncertain parameters are represented as triangular fuzzy numbers handled through possibility theory at a confidence level of χ = 0.85, yielding a tractable crisp equivalent solved using LINGO 18.0. A linear weighted Pareto method identifies the optimal economic-environmental trade-off across 11 weight combinations. Results The model is validated through a case study of the Riyadh metropolitan area comprising 34 candidate network nodes. At the preferred compromise weight combination ( w 3 , w 2 ) = (0.7, 0.3), the construction and operating cost is SAR 24,314.70 thousand and the environmental cost is SAR 815.24 thousand. Relative to the purely economic optimum, an incremental economic expenditure of only SAR 0.48 thousand (less than 0.002% of total costs) reduces environmental costs by SAR 35.12 thousand (4.1%), demonstrating that substantial ecological gains are achievable at virtually negligible economic sacrifice. Discussion The proposed framework provides a quantitative decision-support tool aligned with Saudi Arabia's 2060 net-zero target and directly supports SDG 9, SDG 12, and SDG 13.