Decision analysis with classic and fuzzy EDAS modifications

Decision analysis with classic and fuzzy EDAS modifications Comp. Appl. Math. https://doi.org/10.1007/s40314-018-0652-0 Decision analysis with classic and fuzzy EDAS modifications 1 1 Galina Ilieva · Tania Yankova · Stanislava Klisarova-Belcheva Received: 3 December 2017 / Revised: 9 May 2018 / Accepted: 15 May 2018 © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2018 Abstract In this paper, we introduce L metrics in evaluation based on distance from average solution method for multi-criteria decision making. The strength of the proposed modification stems from the following advantages brought by its new distance measures: (1) capability for working with varied statistical data types; (2) increased sensitivity when comparing values of similar magnitudes; and (3) minimized influence of large differences between elements. We also present a variant of this algorithm that is suitable for trapezoidal fuzzy numbers. The merit of the new fuzzy modification is reduced time complexity due to the proposed calculation simplifications. The effectiveness and practicality of these new extensions are illustrated by three data sets for the best alternative selection. The results show that the modifications produce equal or very similar ranking in comparison with original algorithm and other well-known multi-criteria decision-making methods. Keywords MCDM · EDAS method · Distance metrics · Trapezoidal fuzzy sets Mathematics http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational and Applied Mathematics Springer Journals

Decision analysis with classic and fuzzy EDAS modifications

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Publisher
Springer International Publishing
Copyright
Copyright © 2018 by SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional
Subject
Mathematics; Applications of Mathematics; Computational Mathematics and Numerical Analysis; Mathematical Applications in the Physical Sciences; Mathematical Applications in Computer Science
ISSN
0101-8205
eISSN
1807-0302
D.O.I.
10.1007/s40314-018-0652-0
Publisher site
See Article on Publisher Site

Abstract

Comp. Appl. Math. https://doi.org/10.1007/s40314-018-0652-0 Decision analysis with classic and fuzzy EDAS modifications 1 1 Galina Ilieva · Tania Yankova · Stanislava Klisarova-Belcheva Received: 3 December 2017 / Revised: 9 May 2018 / Accepted: 15 May 2018 © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2018 Abstract In this paper, we introduce L metrics in evaluation based on distance from average solution method for multi-criteria decision making. The strength of the proposed modification stems from the following advantages brought by its new distance measures: (1) capability for working with varied statistical data types; (2) increased sensitivity when comparing values of similar magnitudes; and (3) minimized influence of large differences between elements. We also present a variant of this algorithm that is suitable for trapezoidal fuzzy numbers. The merit of the new fuzzy modification is reduced time complexity due to the proposed calculation simplifications. The effectiveness and practicality of these new extensions are illustrated by three data sets for the best alternative selection. The results show that the modifications produce equal or very similar ranking in comparison with original algorithm and other well-known multi-criteria decision-making methods. Keywords MCDM · EDAS method · Distance metrics · Trapezoidal fuzzy sets Mathematics

Journal

Computational and Applied MathematicsSpringer Journals

Published: Jun 1, 2018

References

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