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Multi-criteria decision-making with probabilistic hesitant fuzzy information based on expected multiplicative consistency

机译:基于预期乘法一致性的概率犹豫不决的信息的多标准决策

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摘要

This study presents a multi-criteria decision-making method that considers expected multiplicative consistency and a consensus reaching process with probabilistic hesitant fuzzy information. The concept of expected multiplicative consistent probabilistic hesitant fuzzy preference relation (PHFPR) is defined on the basis of multiplicative transitivity, and a theorem is developed to obtain the score values of complete expected multiplicative consistent PHFPR. Subsequently, a consistency index of individual PHFPR is proposed by using the distance between individual PHFPR and the score values of its complete expected multiplicative consistent PHFPR. When the individual PHFPR consistency level does not meet the expected value, an iteration algorithm is designed to improve its consistency level and obtain an acceptable one. Furthermore, a group consensus index is proposed according to the distance between the individual acceptable multiplicative consistent PHFPR and the score values of collective PHFPR. An iteration algorithm is designed to improve the consensus level when it does not reach the threshold value. Several numerical examples are provided to demonstrate the effectiveness of the proposed method, and a comparative study involving other methods is conducted with the same numerical examples.
机译:本研究提出了一种多标准的决策方法,其考虑了乘法犹豫不决的模糊信息的预期乘法一致性和达成过程。预期乘法一致的概率犹豫不决的模糊偏好关系(PHFPR)的概念是基于乘法传递性定义的,并且开发了定理以获得完整的预期乘法一致PHFPR的分数值。随后,通过使用个体PHFPR之间的距离和其完整的预期乘法一致PHFPR的距离来提出单个PHFPR的一致性指数。当各个PHFPR一致性水平不符合预期值时,迭代算法旨在提高其一致性水平并获得可接受的级别。此外,根据各个可接受的乘法一致PHFPR与集体PHFPR的分数值之间的距离提出了一组共识指标。迭代算法旨在改善不达到阈值的共识级别。提供了几个数值例子以证明所提出的方法的有效性,并且涉及其他方法的比较研究是用相同的数值实施例进行的。

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