Algorithmic study demonstrates an integrated cubic fuzzy decision framework for waste textile evaluation, suggesting enhanced precision in quality management and fiber recycling decisions.
The performance assessment of waste textiles affects their reuse, and accurately distinguishing the performance of waste textiles and regenerated fibers has become a key issue in quality management. Multi- attribute group decision-making methods are effective tools for evaluating the performance of fibers because they can comprehensively consider various attribute characteristics. This paper describes the uncertainty of multi- objective multi-attribute problems based on the cubic q -rung orthopair fuzzy information, providing stronger generalization ability and representativeness. Firstly, three-dimensional distance measurement method is proposed for cubic fuzzy information, which has both interval and single-value characteristics. By inducing fuzzy operations, the division operation is obtained based on the multiplication operation, and a unique solution evaluation criterion is formulated. Then, the optimized power average and Muirhead mean operators are aggregated in the cubic q -rung orthopair fuzzy environment, and the adjustable parameter ε is added to enhance the applicability of the aggregation model. Further, the critic method is used to compensate for the shortcomings of the entropy weight method, and a cubic q- rung orthopedic fuzzy decision method based on the critic-entropy fusion weight method under three-dimensional distance measurement is proposed, which is applied to the performance evaluation process of waste textiles, thereby providing a more rigorous decision framework and optimizing the decision results through qualitative and quantitative methods. This method provides valuable reference for solving complex uncertainty problems and extending fuzzy decision models to other application areas.
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Du et al. (2026) studied this question.
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