考虑权重信息未知的区间直觉模糊三支群决策方法

本文提出优化视角下专家权重信息未知的区间直觉模糊三支群决策方法。首先利用区间直觉模糊加权平均算子集结不同专家提供的区间直觉模糊损失评价,获得群体综合损失评价结果。以专家个体与群体综合评价相似度越髙,越能反映群体综合评价意见且赋予髙的专家权重为原则,分别构建专家权重信息完全未知和部分已知的权重确定模型。进而建立确定区间直觉模糊三支决策概率阈值对的优化模型,并提出基于专家权重信息未知的区间直觉模糊三支群决策方法。最后,算例分析及比较结果表明所提出方法的有效性。

Interval-valued Intuitionistic Fuzzy Three-Way Group Decisions Considering The Unknown Weight Information

This paper proposes an approach to interval-valued intuitionistic fuzzy three-way group decisions (IVIF3WGDs) under unknown weights of experts from an optimization perspective. We firstut ilize an interval-valued intuitionistic fuzzy linear weight average (IVIFLWA) operator to aggregate interval-valued intuitionistic fuzzy loss evaluations provided by multiple experts, which leads to collective loss evaluation results on an expert group. According to this principle, a larger similarity of expert individual to group better reflects a collective opinion of the group, and we should assign a higher weight of the individual expert. Corresponding mathematical models for determining the weights are further established in two cases of completely and partly unknown weight information. We further construct a pair of optimization models to determine the thresholds in IVIF3WGDs, and develop an IVIF3WGD approach based on unknown weights of experts. Finally, an illustrative example and its comparisons show the effectiveness of the proposed method.