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Please use this identifier to cite or link to this item: https://shodhratna.thapar.edu:8443/jspui/handle/tiet/925
Title: RM approach for ranking of L-R type generalized fuzzy numbers
Authors: Kumar, Amit
Singh, Pushpinder K.
Kaur, Parmpreet
Kaur, Amarpreet
Keywords: L-R type generalized fuzzy number
Ranking function
Issue Date: 2011
Publisher: Springer Nature
Citation: 27
Abstract: Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Syst Appl 36:6833-6842, 2009) is incorrect. The main aim of this paper is to propose a new approach for the ranking of L-R type generalized fuzzy numbers. The proposed ranking approach is based on rank and mode so it is named as RM approach. The main advantage of the proposed approach is that it provides the correct ordering of generalized and normal fuzzy numbers and it is very simple and easy to apply in the real life problems. It is shown that proposed ranking function satisfies all the reasonable properties of fuzzy quantities proposed by Wang and Kerre (Fuzzy Sets Syst 118:375-385, 2001). © 2010 Springer-Verlag.
URI: https://shodhratna.thapar.edu:8443/jspui/handle/tiet/925
ISSN: 14327643
Appears in Collections:MA Journal Articles

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