A method for 2-tuple linguistic dynamic multiple attribute decision making with entropy weight

Abstract

In this paper, we investigate the 2-tuple linguistic dynamic multiple attribute decision making problems with entropy weight. In order to aggregate dynamic 2-tuple linguistic information, some new dynamic Einstein aggregation operators are proposed: the dynamic 2-tuple Einstein weighted averaging (D2TEWA) operator and dynamic 2-tuple Einstein weighted geometric (D2TEWG) operator. Furthermore, some procedures based on the D2TEWA (D2TEWG) operators and 2TWA (2TWG) operators are developed to solve the 2-tuple linguistic dynamic multiple attribute decision making problems with entropy weight. Finally, an illustrative example for evaluating the project's risk is given to verify the developed approach.