army command college of PLA
论文研究了属性权重已知、专家权重未知条件下的概率犹豫模糊多属性群决策问题. 首先, 针对传统概率犹豫模糊距离测度的不足, 提出了改进的新型距离测度, 并对其有效性和合理性进行了数学证明; 其次, 在属性权重已知的前提下, 通过加权算术平均的方式实现了单个专家视角下的概率犹豫模糊信息初次集结; 然后, 基于分差最大化准则构建了专家权重向量求解模型, 并给出了最优解析解; 最后, 在专家权重向量求解的基础上, 基于TODIM方法实现了群体专家视角下的概率犹豫模糊信息二次集结, 并将其应用于作战方案评估优选.
The probabilistic hesitant fuzzy multi-attribute group decision-making (MAGDM) problem, with known attribute weights and unknown expert weights, is studied. First, to overcome the shortcomings of traditional distance measures of probabilistic hesitant fuzzy element (PHFE), new distance measures are proposed, whose effectiveness and validity are mathematically proved; Second, under the premise that attribute weight vector is known, the first probabilistic hesitation fuzzy information aggregation, from the perspective of a single expert, is realized through weighted arithmetic average (WAA); Then, based on the criteria of maximizing score deviation (MSD), a model to solve expert weight is constructed and an analytical solution is derived; Finally, based on TODIM, a probabilistic hesitant fuzzy multi-attribute group decision-making method is developed to realize second information aggregation, which is further applied to the evaluation and selection of combat plans