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
Computational and Applied Mathematics – Springer Journals
Published: Jun 1, 2018
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