The end-of-life (EoL) lithium-ion batteries exhibit a dual nature, functioning simultaneously as hazardous waste and as a high-value second resource. In response, this study develops a scientifically grounded evaluation framework to assess the service efficiency of EoL lithium-ion battery Recycling Centers. To address cognitive and behavioral biases in expert judgment, a fuzzy preference correction model based on Prospect Theory is introduced, accounting for irrational psychological tendencies and limited perspectives during information aggregation. Additionally, to manage incomplete knowledge of criterion weights and interdependencies within complex decision environments, a two-stage optimization model is constructed. The framework is further enhanced through the incorporation of bounded rationality using a Fuzzy Analytic Hierarchy Process with group expert participation. The proposed system is validated through sensitivity and comparative analyses, demonstrating its robustness and practical applicability. Future research may further integrate human–machine expert systems to enhance reasoning capabilities and mitigate the cognitive limitations of human evaluators.
Cheng et al. (Fri,) studied this question.