Abstract
TOPSIS is a multiple criteria method to identify solutions from a finite set of alternatives based upon simultaneous minimization of distance from an ideal positive point and maximization of distance from a negative point. Owing to vague concepts frequently represented in decision data, the crisp value is inadequate to model real-life situations. In this paper, the scoring of each alternative and the weight of each criterion are described by linguistic terms which can be expressed in triangular fuzzy numbers. Then, the ratings and weights assigned by decision makers are averaged and normalized into a comparable scale. A coefficient of variation is defined to determine the ranking order of alternatives by calculating the mean value and standard deviation. A numerical example demonstrates the feasibility of the proposed method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Mehregan, M.R., Safari, H. (2006). Combination of Fuzzy TOPSIS and Fuzzy Ranking for Multi Attribute Decision Making. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_28
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DOI: https://doi.org/10.1007/11785231_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
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