A multi-attribute group decision making method considering both the correlation coefficient and hesitancy degrees under interval-valued intuitionistic fuzzy environment
Group Decision Making
TOPSIS
Similarity (geometry)
Degree (music)
DOI:
10.1016/j.asoc.2021.107187
Publication Date:
2021-02-21T15:10:27Z
AUTHORS (3)
ABSTRACT
Abstract In this paper, we propose a novel multiple attribute group decision making (MAGDM) method based on the correlation coefficient and hesitancy degrees under interval-valued intuitionistic fuzzy environment. Firstly, the conception of individual hesitancy degree and group hesitancy degree are defined to ensure the effective communication of information among group members and overcome the restrictions of the methodology of “majority rule” that some critical information of decision-making would be treated as conflicting opinions to be modified. Secondly, the correlation coefficients of interval-valued intuitionistic fuzzy set (IVIFS) are utilized to measure the similarity instead of distance functions in order to alleviate the drawbacks that do not consider the parameters of hesitancy. Thirdly, we extend the subjective assignment methods on utilizing the IVIFS to assign the weights of different decision makers in order to better address uncertainty in the MAGDM problem. Finally, TOPSIS and Linear programming optimization method are used to calculate the optimal attribute weight, which results in more accurate weights. A real-word application example has been presented to demonstrate the working of the proposed methodology. Moreover, a thorough comparison has been done with related existing works in order to show the validity of this methodology.
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