2-Dimension Linguistic Bonferroni Mean Aggregation Operators and Their Application to Multiple Attribute Group Decision Making

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.