Abstract
With respect to the multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of the 2-dimension linguistic information, a new decision making method is proposed. Firstly, motivated by the ideals of dependent aggregation operator (Z.S. Xu, Dependent uncertain ordered weighted aggregation operators, Information Fusion 9 (2008), 310–316), some 2-dimension linguistic dependent aggregation operators are developed, including a 2-dimension linguistic generalized dependent ordered weighted averaging (2DLGDOWA) operator and a 2-dimension linguistic generalized dependent hybrid weighted averaging (2DLGDHWA) operator which can relieve the influence of unfair 2-dimension linguistic arguments on the aggregated results by assigning low weights to those “false” and “biased” ones. Furthermore, some desirable properties of these operators are studied, such as commutativity, idempotency, monotonicity and boundedness, and some special case are analyzed. Then based on these operators, an approach to multiple attribute group decision making with 2-dimension linguistic information is proposed. Finally, an illustrate example is given to verify the developed approach and to demonstrate its practicality and effectiveness.