Multi-attribute group decision making method based on some trapezoid intuitionistic fuzzy linguistic Bonferroni mean aggregation operators.

The trapezoid intuitionistic fuzzy linguistic (TIFL) variables (TIFLVs) can deal with uncertain information more efficiently and precisely and avoid the information losing and distortion in the decision making process. Bonferroni mean (BM) operator can process the relationship of the inputs. In order to take full advantages of them, in this paper, we extend BM to process TIFL information, and propose the BM operator for TIFLVs (TIFLBM), the weighted BM operator for TIFLVs (TIFLWBM), the geometric BM (GBM) operator for TIFLVs (TIFLGBM), and the weighted GBM operator for TIFLVs (TIFLWGBM). Then some properties and some particular cases of these proposed operators are analyzed. Furthermore, two approaches for multi-attribute group decision making (MAGDM) based on these operators are developed. Finally, by an example, the effectiveness and the advantages of the developed methods are explained.