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TOPSIS Multi-Attribute Decision-Making Model Utilizing Novel Distance Measure of Picture Fuzzy Sets and Its
Supan Yang1, Haiping Ren1,2, Xiaoqing Huang1
1School of Business, Jiangxi University of Science and Technology, Nanchang 330013, China.
Entropy (Basel, Switzerland)
|June 26, 2026
Summary
This study introduces a new picture fuzzy decision-making model for selecting power battery recycling schemes. The novel approach enhances accuracy in complex, uncertain evaluations for a greener circular economy.
Area of Science:
- Decision Sciences
- Environmental Science & Management
- Materials Science & Engineering
Background:
- Power battery recycling is crucial for the new energy industry and circular economy goals.
- Evaluating recycling schemes involves complex factors and ambiguous, uncertain information.
- Traditional fuzzy sets may lose information in uncertain decision-making scenarios.
Purpose of the Study:
- To develop a novel multi-attribute decision-making model for power battery recycling scheme selection.
- To address uncertainties and ambiguities inherent in evaluating recycling processes.
- To enhance decision-making accuracy using picture fuzzy sets and a new distance measure.
Main Methods:
- Proposed a novel picture fuzzy distance measure based on the Bray-Curtis distance.
- Integrated the proposed distance measure with the TOPSIS method to create a new decision-making model.
- Utilized picture fuzzy sets to represent membership, neutrality, and non-membership dimensions of uncertainty.
Main Results:
- Demonstrated the effectiveness and feasibility of the proposed model through a case study on electric vehicle power battery recycling.
- Sensitivity analysis confirmed the model's stability and robustness against parameter variations.
- The novel picture fuzzy distance measure showed superior robustness compared to existing measures.
Conclusions:
- The developed picture fuzzy multi-attribute decision-making model provides reliable support for uncertain decision-making problems.
- The proposed method offers a more comprehensive approach to handling fuzzy information in complex evaluations.
- This research contributes to optimizing power battery recycling strategies for a sustainable circular economy.
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