Comparison of fuzzy numbers based on the probability measure of fuzzy events

Lee, E.S.; Li, R.-J.

doi:10.1016/0898-1221(88)90124-1

Cited by 384 publications

(163 citation statements)

References 9 publications

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“…This concept was first proposed by Jain [7]. Some of the literatures that describe different approach of ranking fuzzy quantities are [1,3,4,10,[13][14][15]. Recently, ranking of trapezoidal fuzzy numbers based on the shadow length has been discussed by Pour et al [12].…”

Section: Introductionmentioning

confidence: 99%

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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Section: Introductionmentioning

confidence: 99%

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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“…Step 5: the fuzzy prioritization technique of Lee and Li (1988) are described for comparison of depreciation methods. These steps are shown in Fig.…”

Section: Research Methods and Stepsmentioning

confidence: 99%

“…Variety of methods has been proposed for prioritizing fuzzy numbers (Asady, 2010;Asady & Zendehnam, 2007;Cheng, 1998;Chu & Tsao, 2002;Nejad & Mashinchi, 2011;Wang & Lee, 2008). We have employed the Lee and Li (1988) method of prioritizing fuzzy numbers in this article. In this method, fuzzy numbers are compared using two criterions: (1) fuzzy number mean and (2) fuzzy number dispersion.…”

Section: Ranking Fuzzy Numbersmentioning

confidence: 99%

Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

Khalili¹,

Mehrjerdi²,

Zare³

2014

10.5267/j.dsl

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“…Express the fuzzy matrix C by three matrices C l , C m and C u according to (15) and (16 ). ,..., 2 , 1 ( m i g i = More proposals for ranking fuzzy numbers exist in the literature, and here is used Lee and Le's [14] method improved by Cheng [15].…”

Section: Steps In the Execution Of The Fuzzy Ahpmentioning

confidence: 99%

“…-Generalized spread (standard deviation) According to Lee and Li [14], a fuzzy number with a higher mean value and, at the same time, a lower spread is ranked better. However, it is not easy to compare two fuzzy numbers when one of them has a higher mean value and, at the same time, a higher spread and the other has a lower mean and, at the same time, a lower spread.…”

Section: Steps In the Execution Of The Fuzzy Ahpmentioning

confidence: 99%

Application of fuzzy AHP method based on eigenvalues for decision making in construction industry

Praščević

Prascevic

2016

Teh. vjesn.

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Original scientific paper The Analytic Hierarchy Process (AHP) has found wide application for multicriteria decision making (MCDM) in various areas. In the paper is given a short survey of the AHP application for decision making in the construction industry and realisation of construction projects. Authors have proposed a method based on the eigenvalue and eigenvector of the fuzzy comparison matrices for determination of local and global priorities of decision alternatives. These eigenvalues are determined using expected values of fuzzy numbers and their products. These fuzzy eigenvalues and eigenvectors are in further procedure applied for ranking the alternatives. Comparing the final ranks of alternatives, obtained according to proposed method and some other methods, the authors found good agreement. The fuzzy AHP, in comparison with AHP with crisp numbers, gives more complete, flexible and realistic results. A case study of the optimal selection of the structural system for a large industrial hall is presented in the paper. Keywords: construction industry; fuzzy AHP; fuzzy number; multicriteria decision making Primjena neizrazite AHP metode utemeljene na vlastitim vrijednostima za donošenje odluka u građevinarstvuIzvorni znanstveni članak Analitički hijerarhijski proces (AHP) našao je široku primjenu za višekriterijsko donošenje odluka (MCDM) u različitim područjima. U radu je dan kratak osvrt na primjenu AHP metode za donošenje odluka u građevinarstvu i realizaciji građevinskih projekata. Autori su predložili metodu za određivanje vlastitih vrijednosti i vlastitih vektora neizrazitih (fuzzy) matrica komparacije za nalaženje lokalnih i globalnih prioriteta alternativa odlučivanja. Vlastite vrijednosti se određuju uporabom očekivane vrijednosti neizrazitih (fuzzy) brojeva i njihovih produkata. Dobivene vlastite vrijednosti i vlastiti vektori se u daljnjoj proceduri primjenjuju za rangiranje alternativa. Uspoređujući konačne rangove alternativa koji su dobiveni prema predloženoj metodi i nekim drugim metodama, autori su našli dobru suglasnost. AHP sa neizrazitim brojevima, u uspoređenju sa AHP sa izrazitim brojevima, daje kompletnije, fleksibilnije i realističnije rezultate. U radu je priložena studija slučaja optimalnog izbora konstruktivnog sustava jedne industrijske hale.

show abstract

Comparison of fuzzy numbers based on the probability measure of fuzzy events

Cited by 384 publications

References 9 publications

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

Application of fuzzy AHP method based on eigenvalues for decision making in construction industry

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