Hesitant Fuzzy Multi-Attribute Decision Making Based on TOPSIS With Entropy-Weighted Method

Qiaoping SUN, Jiewen OUYANG

Abstract


Hesitant fuzzy set (HFS), which allows the membership degree of an element to be a set of several possible values, it has attracted more and more attention due to its powerfulness in representing uncertainty. In this paper, we proposed an approach based on TOPSIS and entropy-weighted method for solving multi-attribute decision making (MADM) problems under hesitant fuzzy environment and the attribute weights is complete unknown. First, we introduce the basic concepts of HFSs. Then, we determine the attribute weights through entropy-weighted method under hesitant fuzzy information. Then, the similarity degree of every alternative with hesitant fuzzy positive ideal solution is displayed to rank all the alternatives. Finally, a numerical example is given to illustrate the effectiveness and feasibility of the proposed method.


Keywords


MADM; Score function; HFS; Entropy-weighted method; TOPSIS

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References


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DOI: http://dx.doi.org/10.3968/n

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