Multiattribute group decision making based on intuitionistic fuzzy partitioned Maclaurin symmetric mean operators

In this paper, we propose a new multiattribute group decision making (MAGDM) method based on the proposed weighted partitioned Maclaurin symmetric mean (IFWPMSM) operators for intuitionistic fuzzy numbers (IFNs). Firstly, motivated by the partitioned Bonferroni mean (PBM) and the Maclaurin symmetric mean (MSM), we present the partitioned MSM (PMSM) operator considering the hypothesis that all attributes can be cut into some groups, where the attributes in the same group are relevant to other multiple attributes of the same group, but the attributes in different groups are irrelevant. Then, we present its characteristics and some special cases. Then, we generalize the PMSM operator to propose the intuitionistic fuzzy PMSM (IFPMSM) operator for IFNs and its weighted form (IFWPMSM) for IFNs. Then, we present several characteristics and special examples of the presented IFPMSM operator and the proposed IFWPMSM operator. Finally, we propose a new MAGDM method based on the proposed IFWPMSM operator and make a comparison with the existing approaches to interpret the usability and the validity of the proposed method.