ABSTRACT
In this paper, we investigate the multiple attribute group decision making problems under linguistic environment, in which the information about attribute weights is unknown completely, and the attribute values (elements in each individual decision matrix) are in the form of linguistic variables. We first utilize the linguistic weighted averaging (LWA) operator to aggregate each individual linguistic decision matrix into a collective linguistic decision matrix. Then, we establish a single-objective optimization model maximizing deviations of the collective attribute values of all alternatives. By solving the model, a simple formula for determining attribute weights is obtained, and a practical procedure for ranking alternatives is also developed.
