Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method

Abstract

To provide a larger space for decision makers, q-rung orthopair fuzzy sets (q-ROFS) can express their uncertain information. As a generalization of the algebraic operations, and the Einstein t-conorm and t-norm, Hamacher operations have become significant in aggregation theory. In order to accurately integrate the input arguments of decision makers, the relation pattern between the arguments must be considered. In this paper, we analyze both the independent and interdependent relationship that exist between the input arguments based on the arithmetic mean and the Maclaurin symmetric mean (MSM) respectively. To be specific, we develop some new Hamacher operations for q-ROFS. In light of these operational laws, we further propose some q-rung orthopair fuzzy Hamacher aggregation operators, i.e., the q-rung orthopair fuzzy Hamacher average (q-ROFHA) operator, the weighted q-rung orthopair fuzzy Hamacher average (Wq-ROFHA) operator, the q-rung orthopair fuzzy Hamacher Maclaurin symmetric mean (q-ROFHMSM) operator and the weighted q-rung orthopair fuzzy Hamacher Maclaurin symmetric mean (Wq-ROFHMSM) operator. Meanwhile, some special cases and properties are examined. To solve q-rung orthopair fuzzy multiple attribute group decision making (q-ROFMAGDM) problems, we design a novel approach according to the Evaluation Based on Distance from Average Solution (EDAS) method. At the same time, with the aid of the best-worst method (BWM), we propose a new way to determine the attribute weight information. With respect to a mobile payment platform selection problem, we test the robustness and reliability of our proposed methodology.