梯形值直觉模糊数类的Dombi加权几何聚集算子及其在多属性群决策中的应用

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Bibhuti Bhusana Meher, Jeevaraj S, Melfi Alrasheedi
{"title":"梯形值直觉模糊数类的Dombi加权几何聚集算子及其在多属性群决策中的应用","authors":"Bibhuti Bhusana Meher,&nbsp;Jeevaraj S,&nbsp;Melfi Alrasheedi","doi":"10.1007/s10462-025-11200-2","DOIUrl":null,"url":null,"abstract":"<div><p>The trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are vital in dealing with real-life decision-making problems (containing uncertainty and vagueness) in engineering and management. The study of aggregation operators on the set of trapezoidal-valued intuitionistic fuzzy numbers is essential for solving decision-making problems modelled under a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. Since TrVIFNs are the generalization class of different types of intuitionistic fuzzy numbers. The main contribution of this paper is to introduce the idea of Dombi t-norm and Dombi t-conorm based aggregation operators on the class of TrVIFNs. In this paper, firstly, we develop a Trapezoidal-Valued Intuitionistic Fuzzy Dombi Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Order Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Hybrid Geometric operator, and we establish mathematical properties through various theorems. Secondly, we propose a multiattribute group decision-making algorithm, such as a trapezoidal-valued multiattribute group decision-making algorithm that uses the proposed aggregation operators. Thirdly, we show the applicability of the proposed decision-making method in solving a multiattribute group decision-making problem involving the photovoltaic site selection. Further, we discuss the sensitivity analysis of the proposed algorithms to demonstrate their stability and reliability. Finally, we show the efficacy of the proposed decision-making approach by comparing it with a few familiar group decision-making methods.</p></div>","PeriodicalId":8449,"journal":{"name":"Artificial Intelligence Review","volume":"58 7","pages":""},"PeriodicalIF":10.7000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10462-025-11200-2.pdf","citationCount":"0","resultStr":"{\"title\":\"Dombi weighted geometric aggregation operators on the class of trapezoidal-valued intuitionistic fuzzy numbers and their applications to multi-attribute group decision-making\",\"authors\":\"Bibhuti Bhusana Meher,&nbsp;Jeevaraj S,&nbsp;Melfi Alrasheedi\",\"doi\":\"10.1007/s10462-025-11200-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are vital in dealing with real-life decision-making problems (containing uncertainty and vagueness) in engineering and management. The study of aggregation operators on the set of trapezoidal-valued intuitionistic fuzzy numbers is essential for solving decision-making problems modelled under a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. Since TrVIFNs are the generalization class of different types of intuitionistic fuzzy numbers. The main contribution of this paper is to introduce the idea of Dombi t-norm and Dombi t-conorm based aggregation operators on the class of TrVIFNs. In this paper, firstly, we develop a Trapezoidal-Valued Intuitionistic Fuzzy Dombi Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Order Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Hybrid Geometric operator, and we establish mathematical properties through various theorems. Secondly, we propose a multiattribute group decision-making algorithm, such as a trapezoidal-valued multiattribute group decision-making algorithm that uses the proposed aggregation operators. Thirdly, we show the applicability of the proposed decision-making method in solving a multiattribute group decision-making problem involving the photovoltaic site selection. Further, we discuss the sensitivity analysis of the proposed algorithms to demonstrate their stability and reliability. Finally, we show the efficacy of the proposed decision-making approach by comparing it with a few familiar group decision-making methods.</p></div>\",\"PeriodicalId\":8449,\"journal\":{\"name\":\"Artificial Intelligence Review\",\"volume\":\"58 7\",\"pages\":\"\"},\"PeriodicalIF\":10.7000,\"publicationDate\":\"2025-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10462-025-11200-2.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence Review\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10462-025-11200-2\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence Review","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10462-025-11200-2","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

梯形值直观模糊数(Trapezoidal-valued intuitionistic fuzzy numbers,TrVIFNs)对于处理工程和管理领域的现实决策问题(包含不确定性和模糊性)至关重要。研究梯形值直观模糊数集合上的聚合算子对于解决在梯形值直观模糊(TrVIF)环境下建模的决策问题至关重要。因为 TrVIFN 是不同类型直观模糊数的泛化类。本文的主要贡献是在 TrVIFN 类中引入了基于 Dombi t-norm 和 Dombi t-conorm 的聚合算子的思想。本文首先提出了梯形值直觉模糊 Dombi 加权几何算子、梯形值直觉模糊 Dombi 有序加权几何算子、梯形值直觉模糊 Dombi 混合几何算子,并通过各种定理建立了其数学性质。其次,我们提出了一种多属性群体决策算法,如梯形值多属性群体决策算法,该算法使用了所提出的聚合算子。第三,我们展示了所提决策方法在解决涉及光伏选址的多属性群体决策问题中的适用性。此外,我们还讨论了所提算法的灵敏度分析,以证明其稳定性和可靠性。最后,我们通过将所提决策方法与几种熟悉的群体决策方法进行比较,展示了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dombi weighted geometric aggregation operators on the class of trapezoidal-valued intuitionistic fuzzy numbers and their applications to multi-attribute group decision-making

The trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are vital in dealing with real-life decision-making problems (containing uncertainty and vagueness) in engineering and management. The study of aggregation operators on the set of trapezoidal-valued intuitionistic fuzzy numbers is essential for solving decision-making problems modelled under a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. Since TrVIFNs are the generalization class of different types of intuitionistic fuzzy numbers. The main contribution of this paper is to introduce the idea of Dombi t-norm and Dombi t-conorm based aggregation operators on the class of TrVIFNs. In this paper, firstly, we develop a Trapezoidal-Valued Intuitionistic Fuzzy Dombi Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Order Weighted Geometric operator, Trapezoidal-Valued Intuitionistic Fuzzy Dombi Hybrid Geometric operator, and we establish mathematical properties through various theorems. Secondly, we propose a multiattribute group decision-making algorithm, such as a trapezoidal-valued multiattribute group decision-making algorithm that uses the proposed aggregation operators. Thirdly, we show the applicability of the proposed decision-making method in solving a multiattribute group decision-making problem involving the photovoltaic site selection. Further, we discuss the sensitivity analysis of the proposed algorithms to demonstrate their stability and reliability. Finally, we show the efficacy of the proposed decision-making approach by comparing it with a few familiar group decision-making methods.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信