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Research Article

Fabric Selection Based on Sine Trigonometric Aggregation Operators Under Pythagorean Fuzzy Uncertainty

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Pages 13928-13942 | Published online: 05 Sep 2022
 

ABSTRACT

In the textile industry, selecting the optimal fabric is crucial in the design and production process. The multiple-criteria decision-making (MCDM) technique has been applied to address fabric selection problems. Because the sine trigonometry function maintains the periodicity and symmetry of the origin in nature, it satisfies the preferences of experts over multiple parameters. Considering the advantages of the sine trigonometry function, we introduce sine trigonometry Pythagorean fuzzy sets (ST-PFSs) and weighted averaging (ST-PFWA) and geometric (ST-PFWG) aggregation operators (AOs). Additionally, we propose a novel method based on ST-PFWA and ST-PFWG AOs to solve two different types of fabric selection MCDM problems. The first problem is provided by Pythagorean fuzzy numbers (PFNs), and we apply the proposed method to address the issue and conduct a comparative analysis with other PFS AOs. The second problem is offered with crisp values, and we apply a PFS linguistic term transform system to convert the values into PFNs. Then, we apply ST-PFWA and ST-PFWG AOs to settle the problem and perform a comparative analysis among different PFS linguistic terms. The complete ranking results illustrate that our proposed methodology is more efficient and reliable than previous approaches and can be used in other textile fields.

摘要

在纺织工业中, 选择最佳面料是设计和生产过程中的关键. 多准则决策(MCDM) 技术已用于解决织物选择问题. 由于正弦三角函数在本质上保持原点的周期性和对称性, 因此它满足专家对多个参数的偏好. 考虑到正弦三角函数的优点, 我们引入了正弦三角-毕达哥拉斯模糊集(ST-PFSs) 、加权平均(ST-PFWA) 和几何(ST-PFWG) 聚集算子(AOs). 此外, 我们提出了一种基于ST-PFWA和ST-PFWG AOs的新方法来解决两种不同类型的织物选择MCDM问题. 第一个问题是由毕达哥拉斯模糊数(PFN) 提供的, 我们将所提出的方法用于解决该问题, 并与其他PFS AO进行了比较分析. 第二个问题提供了清晰的值, 我们应用PFS语言术语转换系统将这些值转换为PFN. 然后, 我们应用ST-PFWA和ST-PFWG AOs来解决这个问题, 并对不同的PFS语言术语进行了比较分析. 完整的排序结果表明, 我们提出的方法比以前的方法更有效、更可靠, 并可用于其他纺织领域.

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 111-2410-H-182-012-MY3) 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).

Ethical approval

The authors declare that they have no conflicts of interest. This article does not contain any studies involving animals performed by any of the authors. This article does not contain any studies involving human participants performed by any of the authors.

Additional information

Funding

This study was supported by the Ministry of Science and Technology, Taiwan (MOST 111-2410-H-182-012-MY3) and Chang Gung Memorial Hospital, Linkou, Taiwan (BMRP 574); National Science and Technology Council, Taiwan [MOST 111-2410-H-182-012-MY3]

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