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Consensus Building for Probabilistic Hesitant Fuzzy Preference Relations with Expected Additive Consistency

机译:具有预期加性一致性的概率犹豫模糊偏好关系的共识建立

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摘要

As an extension of hesitant fuzzy element, probabilistic hesitant fuzzy element (PHFE) has received increasing attention. However, some important issues in PHFE utilization remain to be addressed. This study aims to build a consensus among the decision makers for probabilistic hesitant fuzzy preference relations (PHFPRs) with expected additive consistency. First, several generalized operations that are suitable for PHFPRs are defined. Then, expected additive consistent PHFPRs are introduced, and a theorem is proposed to obtain them. Second, the consistency index is defined based on the Hausdorff distance of PHFEs to measure whether individual PHFPRs exhibit acceptable expected additive consistency. If not, then an automatic iterative algorithm is designed to obtain acceptable ones. Third, group PHFPR is obtained based on the proposed generalized operations, and then the consensus index is determined according to the Hausdorff distance. If at least one of the consensus levels of the decision makers is lower than a given threshold, then an automatic iterative algorithm is used to update the PHFPRs to reach a predefined consensus level. Finally, a numerical example is provided, and comparative analyses with existing methods are performed to demonstrate the validity of the proposed method in addressing group decision-making problems.
机译:作为犹豫模糊元素的扩展,概率犹豫模糊元素(PHFE)受到越来越多的关注。但是,PHFE利用中的一些重要问题仍有待解决。这项研究旨在在决策者之间建立具有预期相加一致性的概率犹豫模糊偏好关系(PHFPR)的共识。首先,定义了适用于PHFPR的几种通用操作。然后,引入了预期的加性一致PHFPR,并提出了一个定理来获得它们。其次,基于PHFE的Hausdorff距离定义一致性指数,以测量各个PHFPR是否表现出可接受的预期添加剂一致性。如果不是,则设计一种自动迭代算法以获得可接受的算法。第三,基于提出的广义运算获得PHFPR组,然后根据Hausdorff距离确定共识指数。如果决策者的共识水平中的至少一个低于给定阈值,则使用自动迭代算法来更新PHFPR以达到预定义的共识水平。最后,给出了一个数值例子,并与现有方法进行了比较分析,以证明该方法在解决群体决策问题上的有效性。

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