2-Tuple Prioritized Aggregation Operators and Their Application to Multiple Attribute Group Decision Making

Aims: The aim of this paper is to present some 2-tuple prioritized aggregation operators for handling the multiple attribute group decision making problems where there exists a prioritization relationship over the attributes and decision makers. Study Design: Motivated by the idea of the prioritized aggregation (PA) operators, we first develop two 2-tuple prioritized aggregation operators called the 2-tuple prioritized weighted average (2TPWA) operator and the 2-tuple prioritized weighted geometric (2TPWG) operator. Place and Duration of Study: We examine their desirable properties. Methodology: The significant feature of these operators is that they not only deal with the linguistic and interval linguistic information but also take the prioritization relationship among the arguments into account. Results: Then, based on the proposed operators, we propose an approach to multiple attribute group decision making under linguistic environment in which the attributes and decision makers are in different priority level. Conclusion: Finally, an illustrative example is employed to show the reasonableness and effectiveness of the proposed approach.