Dynamic uncertain linguistic weighted averaging operator

With respect to multiple periods multiple attribute decision making problems with uncertain linguistic preference relations. Definition and some operational laws of uncertain linguistic variables are introduced, and two new operators called dynamic uncertain linguistic weighted averaging (DULWA) operator and dynamic uncertain linguistic averaging (DULA) operator are presented. A model based on DULWA and DULA operators is developed to solve the multiple periods multiple attribute decision making problems which the attribute values takes the form of uncertain linguistic preference relations collected t different periods. Then the DULWA and DULA operators are utilized to aggregate the overall uncertain linguistic preference corresponding to each alternative, and then rank the alternatives and select the most desirable one(s). Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.