Approaches Based on Interval Type-2 Fuzzy Aggregation Operators for Multiple Attribute Group Decision Making

Abstract

This paper aims to develop interval type-2 fuzzy aggregation operators including interval type-2-dependent ordered weighted averaging (IT2DOWA) operator and interval type-2 power averaging (IT2PA) operator. Properties of new aggregation operators are discussed, and interval type-2 weighted-dependent ordered weighted averaging (IT2WDOWA) operator and interval type-2 power averaging (IT2WPA) operator are presented by combining objective weights with subjective weights. Moreover, we utilize new operators to develop approaches for multiple attribute group decision making (MAGDM) with interval type-2 fuzzy numbers. Finally, we give an illustrative example to verify the developed approaches and simultaneously, some existing methods are referred to make comparison in order to demonstrate practicality and effectiveness of new ones. The primary contribution of this paper is twofold. One is to develop some new aggregation operators whose aggregation weights in MAGDM mainly depend on the relationship of aggregated interval type-2 fuzzy numbers by using different deviation measures. Another is to propose approaches with new interval type-2 aggregation operators to MAGDM problems, which begin with natural linguistic evaluation and EKM algorithms.