Comp. Appl. Math.
Decision analysis with classic and fuzzy EDAS
· Tania Yankova
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 Subject Classiﬁcation 03E72
Decision making under conditions of uncertainty and imprecise data is a complex task in
modern organizations and it requires sophisticated methods and instruments. The purpose of
Communicated by Anibal Tavares de Azevedo.
Faculty of Economics and Social Sciences, University of Plovdiv Paisii Hilendarski, 24 Tzar Asen,
4000 Plovdiv, Bulgaria