Ranking fuzzy numbers based on epsilon-deviation degree

NCUIR > School of Management at National Central University > Department of Business Administration > journal & Dissertation > Item 987654321/103101

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/103101

Title:	Ranking fuzzy numbers based on epsilon-deviation degree
Authors:	沈建文;Yu, Vincent F.;Chi, Ha Thi Xuan;Shen, Chien-wen
Contributors:	管理學院企業管理學系
Keywords:	Area;Centroid;Decision making;Ranking fuzzy numbers
Date:	2013-06-24
Issue Date:	2026-04-23 11:23:20 (UTC+8)
Publisher:	Elsevier BV;Elsevier B.V
Abstract:	摘要： •An epsilon-deviation degree approach based on deviation degree is proposed.•Overcome the shortcomings of the left and right deviation degree becoming worthless.•Tackle the conflict between ranking order of fuzzy numbers and that of their images.•An optimism index is employed for ranking symmetric fuzzy numbers effectively. Although numerous research studies in recent years have been proposed for comparing and ranking fuzzy numbers, most of the existing approaches suffer from plenty of shortcomings. In particular, they have produced counter-intuitive ranking orders under certain cases, inconsistent ranking orders of the fuzzy numbers’ images, and lack of discrimination power to rank similar and symmetric fuzzy numbers. This study's goal is to propose a new epsilon-deviation degree approach based on the left and right areas of a fuzzy number and the concept of a centroid point to overcome previous drawbacks. The proposed approach defines an epsilon-transfer coefficient to avoid illogicality when ranking fuzzy numbers with identical centroid points and develops two innovative ranking indices to consistently distinguish similar or symmetric fuzzy numbers by considering the decision maker's attitude. The advantages of the proposed method are illustrated through several numerical examples and comparisons with the existing approaches. The results demonstrate that this approach is effective for ranking generalized fuzzy numbers and overcomes the shortcomings in recent studies. 出版者： Elsevier B.V 出版日期： 2013-08-01 出處： Applied soft computing, 2013-08, Vol.13 (8), p.3621-3627 版權： 2013 Elsevier B.V. 識別號： ISSN: 1568-4946 識別號： EISSN: 1872-9681 識別號： DOI: 10.1016/j.asoc.2013.03.016
Appears in Collections:	[Department of Business Administration ] journal & Dissertation

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