Multiple Attribute Group Decision Making with Linguistic Information Based on Linguistic Prioritized Operators

In this paper, we propose some linguistic prioritized aggregation operators and uncertain linguistic prioritized aggregation operators for handling the multiple attribute group decision making problems in which the attributes and decision makers are in different priority level. First, we extend the prioritized aggregation (PA) operators [R. R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 48 (2008) 263-274] to linguistic environment and present two linguistic prioritized aggregation operators called the linguistic prioritized weighted average (LPWA) operator and the linguistic prioritized weighted geometric (LPWG) operator. These proposed operators can capture the prioritization phenomenon among the aggregated arguments. Then, some desirable properties of these aggregation operators are examined in detail. We next utilize the proposed operators to develop an approach to multiple attribute group decision making under linguistic environment in which the attributes and decision makers are in different priority level, and a practical example is given to illustrate the practicality and effectiveness of the developed approach.