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preference-ratio
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Fuzzy analytical hierarchy process using preference ratio: A case study for selecting management short course in a business school
, Article International Journal of Industrial Engineering Computations ; Volume 1, Issue 2 , 2010 , Pages 173-184 ; 19232926 (ISSN) ; Sadi Nezhad, S ; Arabi, F ; Sharif University of Technology
2010
Abstract
Analytic Hierarchy Process (AHP) is one of the most popular approaches in the area of multiple attribute decision making (MADM). However, it is not practical any more if input information are fuzzy. In this paper, we propose a new method for fuzzy AHP which is especially useful to make decisions for multiple attribute problems. The method is developed by applying preference ratio concept which makes it practical since it assigns crisp weights and crisp scores to different alternatives. Two algorithms are proposed in this paper: The first one defines crisp and normalized weight by pairwise comparison with fuzzy data while the second one calculates fuzzy consistency ratio. The proposed method...
Fuzzy simple additive weighting method by preference ratio
, Article Intelligent Automation and Soft Computing ; Volume 11, Issue 4 , 2005 , Pages 235-244 ; 10798587 (ISSN) ; Sadi Nezhad, S ; Sharif University of Technology
2005
Abstract
Although simple additive weighting method (SAW) is the most popular approach for classical multiple attribute decision making (MADM), it is not practical any more if information is fuzzy. The existing methods of Fuzzy Simple Additive Weighting method (FSAW) apply defuzzification which distorts fuzzy numbers. Furthermore, most of the methods usually require lengthy and laborious manipulations. In this paper, we develop a new a fuzzy simple additive weighting method for multiple attribute decision making problems. To avoid defuzzification round off errors caused by multiplication or other arithmetic manipulations, fuzzy numbers are ranked prior to any fuzzy arithmetic in this method. The...
Ranking fuzzy numbers by preference ratio
, Article Fuzzy Sets and Systems, Amsterdam ; Volume 118, Issue 3 , 2001 , Pages 429-436 ; 01650114 (ISSN) ; Sadi Nezhad, S ; Sharif University of Technology
Elsevier Science Publishers B.V
2001
Abstract
We propose a ranking method for fuzzy numbers. In this method a preference function is defined by which fuzzy numbers are measured point by point and at each point the most preferred number is identified. Then, these numbers are ranked on the basis of their preference ratio. Therefore, fuzzy numbers are compared relatively and not necessarily one is preferred absolutely over the others. This method is especially designed to evaluate alternatives in multi criteria or multi-attribute decision making. The method is intuitive and can be used to discriminate between numbers easily. The method is specially tailored for triangular fuzzy numbers (TFN) and an algorithm is presented to determine the...