Abstract:

An adaptive consensus model based on linguistic information granulation is presented for group consensus decision making problems with unbalanced fuzzy linguistic preference information. A granular representation of unbalanced linguistic terms is concerned with the interval formation of a family of information granules over the unit interval. In the case of the cutoffs of information granules unknown, individual consistent degree and group consensus degree of granulation are defined. An optimization model to determine the optimal cutoffs of information granules is established with the help of the above two definitions. Group consensus is achieved by constantly adjusting individual preferences through the optimization of the cutoffs. Finally, a group decisionmaking method which is a guarantee of reaching a certain degree of group consensus before aggregating expert opinions is proposed, and also a numerical example illustrates the feasibility and effectiveness of the proposed method.