Uncertain prioritized operators and their application to multiple attribute group decision making

Abstract

In this paper, we investigate the uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Motivated by the idea of prioritized aggregation operators (Yager 2008), we develop some prioritized aggregation operators for aggregating uncertain information, and then apply them to develop some models for uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.