A method based on trust model for large group decision-making with incomplete preference information.

A new method of solving large group decision-making problems with incomplete preference information is proposed in this paper. First, we introduce the trust viewpoint of access control, which belongs to the information technology field. Second, we establish subjective trust degree (i.e., direct trust degree) and objective trust degree (i.e., indirect trust degree) to better evaluate the level of trust and propose a compensation method based on a trust model to transfer the incomplete preference matrix into a complete preference matrix. Third, by adopting the method based on clustering to solve decision makers' weights, a ranking of alternatives is obtained by synthesizing the weights and the complete preference matrix. To obtain a more reasonable clustering result, we redefine the distance similarity formula based on analysis of the previous problems, then combine it with cosine similarity to propose a double clustering model. Finally, a numerical example is used to demonstrate the effectiveness of the proposed method in this paper and comparison and analysis are conducted.