Service efficiency assessment of end-of-life lithium-ion battery recycling centers based on a fuzzy preference correction model

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.

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Publication Details

Journal
Energy & Environment
Published
2026-03-13
DOI
https://doi.org/10.1177/0958305x261428676
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
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article

Service efficiency assessment of end-of-life lithium-ion battery recycling centers based on a fuzzy preference correction model

Zhongwei Cheng, Kèyù Zhü, Lifeng Yang
Energy & Environment
Multi-Criteria Decision Making
article

Service efficiency assessment of end-of-life lithium-ion battery recycling centers based on a fuzzy preference correction model

Zhongwei Cheng, Kèyù Zhü, Lifeng Yang
article en

Abstract

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.

Energy & Environment
Fuyang Normal University (CN), Hefei University of Technology (CN)
Openalex Percentile: Top 26%
Multi-Criteria Decision Making
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