2-dimension linguistic bonferroni mean aggregation operators and their application to multiple attribute group decision making

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Abstract

The aim of this paper is to provide a multiple attribute group decision making (MAGDM) method based on the 2-dimension linguistic weight Bonferroni mean aggregation (2DLWBMA) operator. Firstly, the new operations of 2-dimension linguistic variables are defined. Then, the 2-dimension linguistic Bonferroni mean aggregation operator is proposed to describe the correlations of input arguments. Subsequently, the 2DLWBMA operator is investigated to consider the importance of attributes. Furthermore, a novel MAGDM method is introduced and two illustrative examples are given.

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Zhao, J., & Zhu, H. (2019). 2-dimension linguistic bonferroni mean aggregation operators and their application to multiple attribute group decision making. International Journal of Computational Intelligence Systems, 12(2), 1557–1574. https://doi.org/10.2991/ijcis.d.191125.001

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