基于高度残缺信息的分布式语言信任网络群决策方法

针对缺失的分布式语言信任社会矩阵以及高度残缺的评价信息, 提出一种新的分布式语言信任网络群决策方法。首先, 提出了一种分布式语言信任传递模型以填充分布式语言信任社会矩阵中的缺失值。其次, 定义了基于分布式语言信任社会矩阵的个体信任中心度和群体信任中心度, 并在此基础上提出了确定评价网络中专家权重的方法。再者, 鉴于决策矩阵中评价信息存在高度残缺的情形, 利用K-近邻算法评估残缺的评价信息, 并基于分布式语言信任函数的距离测度提出一种改进的逼近理想解排序(technique for order preference by similarity to an ideal solution, TOPSIS)法。最后, 通过外卖服务平台性价比的综合评估验证该群决策方法的可行性和有效性。

Group decision making method for distributed linguistic trust network based on highly incomplete information

Aiming at the missing distributed linguistic trust social matrix and highly incomplete evaluation information, a new group decision-making method for distributed linguistic trust network is proposed. Firstly, a distributed linguistic trust propagation model is proposed to fill the missing values in the distributed linguistic trust social matrix. Secondly, the individual trust centrality and the group trust centrality based on the distributed linguistic trust social matrix are defined, and a method to determine the weight of experts in the evaluation network is proposed. Furthermore, in view of the highly incomplete evaluation information in the decision matrix, the K-nearest neighbor algorithm is used to evaluate the incomplete evaluation information, and an improved technique for order preference by similarity to an ideal solution (TOPSIS) method is proposed based on the distance measure of distributed linguistic trust function. Finally, the feasibility and the effectiveness of the group decision making method are verified by the comprehensive evaluation of the cost performance of the takeout service platform.