基于新型距离测度的概率语言多属性群决策方法

研究属性权重和专家权重均未知条件下的概率语言多属性群决策问题.首先,针对传统概率语言术语集距离测度的不足,提出改进的距离测度,并证明其性质和优越性.其次,基于新的距离公式,定义决策者的平均相似度,并结合专家之间的信任度矩阵计算每个属性下决策者的综合权重;构建基于相似-信任分析的群体共识调节模型,尽可能保留各属性下权威专家的意见;考虑到属性之间的相关性以及各个属性的重要程度,构建基于广义Choquet积分和离差最大化法的主客观综合赋权模型.随后,在新的距离测度的基础上,结合TODIM方法构建概率语言多属性群决策框架,实现对多个备选方案的排序.最后,以光伏电站的选址为例,验证所提出方法的有效性和合理性.

Probabilistic linguistic multi-attribute group decision making method based on new distance measure

Probabilistic linguistic multi-attribute group decision making with unknown attribute weights and expert weights is studied. Firstly, aiming at the deficiency of the distance measure of the traditional probabilistic linguistic term sets, an improved distance measure is proposed, and its properties and advantages are proved. Secondly, based on the new distance measure, the average similarity of decision makers is defined, and the comprehensive weight of decision makers under each attribute is calculated by combining the trust matrix between experts. A group consensus adjustment model based on similarity-trust analysis is constructed to retain the opinions of authoritative experts under each attribute as much as possible. Considering the correlation between attributes and the importance of each attribute, this paper constructs a subjective and objective comprehensive weighting model based on the generalized Choquet integral and deviation maximization method. Then, based on the new distance measure, a probabilistic linguistic multi-attribute group decision framework is constructed by combining the TODIM method to rank multiple alternatives. Finally, the site selection of photovoltaic power station is taken as an example to verify the effectiveness and rationality of the proposed method.