Pythagorean Fuzzy Sets Combined with the PROMETHEE Method for the Selection of Cotton Woven Fabric

Identifying and selecting the best cotton fabric from a series of available samples is a challenging multicriteria decision-making (MCDM) problem that includes fuzziness and uncertainty. Pythagorean fuzzy sets (PFSs) are widely used to manage complex and uncertain MCDM issues. The Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) is a widely used classical MCDM to assess and rank alternatives. In this study, we use the PROMETHEE approach to solve a real case of ranking cotton fabrics in a PFS environment, where alternatives are compared based on the PFS linguistic scales, and a score function is used as a defuzzification function. A comparative analysis is also performed with different score functions. The ranking results of the proposed PF-PROMETHEE method correlate strongly with other score functions, which indicates that the PF-PROMETHEE method is feasible and effective. The salient contributions of the PF-PROMETHEE method are as follows: (1) the method can manage uncertainty better than other methods; (2) uncertainty is evaluated by linguistic scales in the PF environment; (3) the method can effectively select cotton woven fabric; and (4) the method is applicable to a wide variety of MCDM problems in the textile industry.

Automated summary

In this study, the PROMETHEE approach is used to rank cotton fabrics, and a comparative analysis of different score functions is performed. The proposed PF-PROMETHEE method shows good ranking accuracy and better ability to handle uncertainty, making it applicable to multicriteria decision-making problems in the textile industry.