基于新型距离测度的概率犹豫模糊多属性群决策方法

研究属性权重已知、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,提出改进的新型距离测度,并对其有效性和合理性进行数学证明;其次,在属性权重向量已知的前提下,通过加权算术平均的方式实现单个专家视角下的概率犹豫模糊信息初次集结,并基于分差最大化准则构建专家权重向量求解模型,采用...

Probabilistic hesitant fuzzy multi-attribute group decision-making based on new distance measure

The paper studies the probabilistic hesitant fuzzy multi-attribute group decision-making(MAGDM) problem under the condition that the attribute weights are known and the expert weights are unknown. Firstly, to overcome the shortcomings of traditional distance measures of the probabilistic hesitant fuzzy elements(PHFEs), improved new distance measures of PHFEs are proposed, whose validity and rationality are mathematically proved. Secondly, under the premise that attribute weights are known, the first aggregation of the probabilistic hesitant fuzzy information, from the perspective of a single expert, is realized through weighted arithmetic averaging(WAA). Thirdly, based on the criteria of maximizing score deviation (MSD), a mathematical model of solving the expert weights is constructed and an analytical solution is further derived, Then, based on the TODIM method, a probabilistic hesitant fuzzy MAGDM method is developed to realize the second aggregation of the probabilistic hesitant fuzzy information, from the perspective of a group of experts. Finally, by taking the fuzzy optimization of army force''s combat plans under the condition of information-based warfare as an example, the feasibility and effectiveness of the proposed interactive MAGDM method are verified.