基于信息粒化的不平衡模糊语言共识模型

Consensus model with unbalanced fuzzy linguistic information based on information granulation

针对不平衡模糊语言偏好信息下的群体共识决策问题,提出了一种基于语言信息颗粒优化的自适应共识模型。该模型将不平衡语言术语以单位区间上一族区间形式的信息粒颗粒表征,在颗粒分割点未知的情形下定义了粒化个体一致度与粒化群体共识度,并利用它们构建了确定信息颗粒最佳分割点的优化模型,通过分割点的寻优自适应调整个体偏好直至共识达成。最后,给出了一种群决策方法,确保在集结专家意见前群体达成一定程度的共识,并通过一个算例说明方法的可行性和有效性。

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 repre-sentation of unbalanced linguistic terms is concerned with the interval formation of a family of information gran-ules over the unit interval.In the case of the cutoffs of information granules unknown,individual consistent de-gree and group consensus degree of granulation are defined.An optimization model to determine the optimal cut-offs 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 pro-posed method.