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基于语言尺度函数和Dombi聚合算子的费马模糊语言术语集及其在多准则群体决策问题中的应用

Fermatean fuzzy Linguistic term set based on linguistic scale function with Dombi aggregation operator and their application to multi criteria group decision -making problem.

作者信息

Barukab Omar, Khan Asghar, Khan Sher Afzal

机构信息

Faculty of Computing and Information Technology, King Abdulaziz University, P.O. Box 411, 21911, Rabigh, Jeddah, Saudi Arabia.

Department of Mathematics, Abdul Wali Khan University, Mardan, 23200, KP, Pakistan.

出版信息

Heliyon. 2024 Aug 20;10(17):e36563. doi: 10.1016/j.heliyon.2024.e36563. eCollection 2024 Sep 15.

DOI:10.1016/j.heliyon.2024.e36563
PMID:39263126
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11387342/
Abstract

The selection of an industrial location is a challenging multiple-criteria decision-making (MCDM) problem that depends on taking a variety of locations as well as incompatible and inconsistent criteria. This paper proposed a comprehensive framework for the strategic selection of industrial locations, considering both quantitative and qualitative aspects. Decision-makers (DMs) have to deal with ambiguous information throughout this process due to a complex decision environment or their insufficient knowledge. We present a new Fermatean Fuzzy (FF) Linguistic term set based on the Dombi aggregation operators (AOs). By combining the FF set with Linguistic variables, the FF Linguistic (FFL) set is an effective approach for thoroughly representing uncertain evaluation information. We establish a basic operational principles and certain aggregation operator under FFL information, such as the FF Linguistic Dombi weighted averaging (FFLDWA) operator FF Linguistic Dombi weighted geometric (FFLDWG) operator and some fundamental properties of these operators with appropriated elaboration. Based on these operators, a multi-criteria group decision-making technique is developed. Finally, we used a numerical example to compare the flexibility of the suggested technique with other existing methods. Thus, by knowing priorities industries, the best site can be selected.

摘要

工业选址是一个具有挑战性的多准则决策(MCDM)问题,它依赖于考虑多种选址以及不相容和不一致的准则。本文提出了一个用于工业选址战略选择的综合框架,兼顾了定量和定性方面。由于决策环境复杂或决策者知识不足,他们在整个过程中必须处理模糊信息。我们基于Dombi聚合算子(AO)提出了一种新的费马模糊(FF)语言术语集。通过将FF集与语言变量相结合,FF语言(FFL)集是一种全面表示不确定评估信息的有效方法。我们建立了FFL信息下的基本运算规则和特定聚合算子,如FF语言Dombi加权平均(FFLDWA)算子、FF语言Dombi加权几何(FFLDWG)算子,并对这些算子的一些基本性质进行了适当阐述。基于这些算子,开发了一种多准则群体决策技术。最后,我们通过一个数值例子将所提技术的灵活性与其他现有方法进行了比较。因此,通过了解优先发展的产业,可以选择最佳选址。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/a9f5cd9b028a/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/f0c2dba4ddc8/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/c8321a135b07/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/711b4a1850d5/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/a86b294aaeca/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/1ea064db4c95/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/d8438dccac7a/gr7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5228/11387342/7dd94821867b/gr9.jpg

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