基于信任机制的不完全信息大群体决策方法

Method for large group decision making with incomplete decision preference information based on trust mechanism

针对不完全偏好信息大群体决策问题,引入访问控制中的信任机制,建立直接信任度与推荐信任度,提出一种基于信任机制的补值方法;分析了基于距离相似度存在的问题,定义了一种新的距离相似度,并与余弦相似度结合,构建了决策偏好二元相似度的相聚模型;利用聚类方法求解决策成员的权重,并与补值后的完整偏好矩阵进行合成,求得决策方案排序.最后,利用一个现有的文献案例验证了所提出方法的有效性和优越性.

For the large group decision making problem with incomplete decision preference information, the trust mechanism belonging to the access control is introduced, the direct trust degree and recommendation trust degree are established, and a compensation method based on the trust mechanism is proposed. With analyzing the problems of previous distance similarity, a new distance formula of similarity is proposed, which is combined with the cosine similarity, and a2-tuple similarity model to clustering is established. Based on the proposed clustering model, the decision makers＇ weight is solved by using the clustering method, and the decision ranking is obtained by the synthesis of weights and the complete preference matrix. Finally, an existing literature case is given to illustrate the effectiveness and advantage of the proposed method.