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Area ranking of fuzzy numbers based on positive and negative ideal points

โœ Scribed by Ying-Ming Wang; Ying Luo


Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
864 KB
Volume
58
Category
Article
ISSN
0898-1221

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โœฆ Synopsis


a b s t r a c t

The maximizing set and minimizing set method is a popular ranking approach for fuzzy numbers, which ranks them based on their left, right and total utilities. This paper presents an alternative ranking approach for fuzzy numbers called area ranking based on positive and negative ideal points, which defines two new alternative indices for the purpose of ranking. The two new indices are defined in terms of a decision maker (DM)'s attitude towards risks and the left and the right areas between fuzzy numbers and the two ideal points. It is shown that the area ranking approach has strong discrimination power and can rank fuzzy numbers that are unable to be discriminated by the maximizing set and minimizing set method. It is also shown that the DM's attitude towards risks may have a significant impact on the ranking of fuzzy numbers. As a side product, a new defuzzification formula is also developed and discussed.


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โœ Yu-Jie Wang; Hsuan-Shih Lee ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 227 KB

In 2002, Chu and Tsao proposed a method to rank fuzzy numbers. They employed an area between the centroid and original points to rank fuzzy numbers; however there were some problems with the ranking method. In this paper, we want to indicate these problems of Chu and Tsao's method, and then propose