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

ABSTRACT

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.

摘要

从一系列可用样本中识别和选择最佳棉织物是一个具有挑战性的多准则决策(MCDM)问题,其中包括模糊性和不确定性. 毕达哥拉斯模糊集(Pythagorean fuzzy sets,PFS)被广泛用于管理复杂且不确定的MCDM问题. 偏好排序组织方法(PROMETHEE)是一种广泛使用的经典MCDM,用于评估和排序备选方案. 在本研究中,我们使用PROMETHEE方法解决了一个在PFS环境中对棉织物进行排名的真实案例,在该案例中,基于PFS语言量表对备选方案进行比较,并使用评分函数作为解模糊函数. 还对不同的评分函数进行了比较分析. 所提出的PF-PROMETHEE方法的排名结果与其他评分函数有很强的相关性,这表明PF-PROMETHEE方法是可行和有效的. PF-PROMETHEE方法的突出贡献如下:(1)与其他方法相比,该方法能够更好地管理不确定性;(2) 在PF环境下,通过语言量表评估不确定性;(3) 该方法能有效地选择棉织物;(4)该方法适用于纺织行业的各种MCDM问题.

KEYWORDS:

• Multicriteria decision-making
• Pythagorean fuzzy sets
• Promethee
• cotton fabrics
• score function
• comparative analysis

关键词:

• 多准则决策
• 毕达哥拉斯模糊集
• 棉织物
• 评分函数
• 比较分析

Acknowledgments

The authors acknowledge the assistance of the respected editor and the anonymous referees for their insightful and constructive comments, which helped to improve the overall quality of the paper. The corresponding author is grateful for grant funding support from the Ministry of Science and Technology, Taiwan (MOST 110-2410-H-182-005) and Chang Gung Memorial Hospital, Linkou, Taiwan (BMRP 574) during the completion of this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Chang Gung Memorial Hospital, Linkou [BMRP 574]; Ministry of Science and Technology, Taiwan [MOST 110-2410-H-182-005].