基于互动与反馈的概率语言多属性群决策模型

针对概率语言多属性群决策问题,提出了基于互动与反馈的概率语言多属性群决策模型。首先定义了概率语言的距离测度和概率语言矩阵的一致性测度,以决策者的总体一致性测度确定决策者的客观权重,结合决策者的主观权重以主客观组合赋权法确定决策者的最终权重;结合概率语言的距离测度改进灰色关联度法,以归一化的属性关联度确定属性权重;为达到群决策中决策者的最大共识度,建立了具有互动与反馈过程的决策模型;最后提出了基于互动与反馈的概率语言多属性群决策模型的决策步骤,并且通过算例分析证明了该模型的有效性与可行性。

Probabilistic Linguistic Multi-attribute Group Decision Making Model Based on Interaction and Feedback

A probabilistic linguistic multi-attribute group decision model based on interaction and feedback is proposed for solving probabilistic linguistic multi-attribute group decision making(MAGDM)problems.Firstly,the distance measure between probabilistic linguistic term sets(PLTSs)and the consistency measure between probabilistic linguistic matrix are defined.Based on the overall consistency of decision makers(DMs),the objective weights of DMs are determined.Combing subjective and objective weights of DMs to determine the final weights of DMs.Grey correlation method is improved based on the distance measure between PLTSs,the attribute weight is determined by the normalized correlation degree of attribute.To maximize the consensus of DMs,a decision making model with interaction and feedback is built.Finally,the decision process of probabilistic linguistic MAGDM model based on interaction and feedback is put forward.Further,the case study is applied to show the effectiveness and feasibility of the model.