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A new group decision making approach based on incomplete probabilistic dual hesitant fuzzy preference relations

机译:基于不完全概率的双估量模糊偏好关系的新组决策方法

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摘要

As an enhanced version of probabilistic hesitant fuzzy sets and dual hesitant fuzzy sets, probabilistic dual hesitant fuzzy sets (PDHFSs) combine probabilistic information with the membership degree and non-membership degree, which can describe decision making information more reasonably and comprehensively. Based on PDHFSs, this paper investigates the approach to group decision making (GDM) based on incomplete probabilistic dual hesitant fuzzy preference relations (PDHFPRs). First, the definitions of order consistency and multiplicative consistency of PDHFPRs are given. Then, for the problem that decision makers (DMs) cannot provide the reasonable associated probabilities of probabilistic dual hesitant fuzzy elements (PDHFEs), the calculation method of the associated probability is given by using an optimal programming model. Furthermore, the consistency level for PDHFPRs is tested according to the weighted consistency index defined by the risk attitude of DMs. In addition, a convergent iterative algorithm is proposed to enhance the unacceptable consistent PDHFPRs’ consistency level. Finally, a GDM approach with incomplete PDHFPRs is established to obtain the ranking of the alternatives. The availability and rationality of the proposed decision making approach are demonstrated by analyzing the impact factors of haze weather.
机译:作为一个增强版的概率犹豫不决的模糊集和双犹豫不决的模糊套装,概率的双重犹豫模糊集(PDHFSS)将概率信息与成员学位和非隶属度相结合,可以更合理和全面地描述提供信息的决策。基于PDHFSS,本文研究了基于不完全概率的双犹豫不决的模糊偏好关系(PDHFPRS)的小组决策(GDM)的方法。首先,给出了订单一致性的定义和PDHFPRS的乘法一致性。然后,对于决策者(DMS)不能提供合理的相关联的概率(PDHFE)的问题,通过使用最佳编程模型给出相关概率的计算方法。此外,根据DMS风险态度定义的加权一致性指数来测试PDHFPRS的一致性水平。另外,提出了一种会聚迭代算法来增强不可接受的一致PDHFPRS的一致性水平。最后,建立了具有不完整PDHFPRS的GDM方法,以获得替代品的排名。通过分析阴霾天气的影响因素来证明拟议决策方法的可用性和合理性。

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