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New extension of TOPSIS method based on Pythagorean hesitant fuzzy sets with incomplete weight information

机译:基于Pythagorean犹豫不决的模糊集的Topsis方法的新扩展

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Pythagorean Hesitant fuzzy set (PHFS) which permits the membership degree and non-membership degree of an element to a set represented by several possible values is deliberated as a powerful tool to express uncertain information in the process of multi-attribute decision making (MADM) problems. In this paper, we propose a novel approach based on TOPSIS method and the maximizing deviation method for solving MADM problems where the evaluation information provided by the decision makers (DMs) is expressed in form of Pythagorean hesitant fuzzy numbers and the information about attribute weights is incomplete. To determine the attribute weight we develop an optimization model based on maximizing deviation method. Finally we provide a practical decision-making problem to demonstrate the implementation process of the proposed method.
机译:佩达哥拉西犹豫的模糊集(PHF)允许元素的成员度和非隶属度到几个可能值所代表的集合,作为一个强大的工具,以表达多属性决策(MADM)过程中的不确定信息 问题。 在本文中,我们提出了一种基于TOPSIS方法的新方法和最大化偏差方法,用于解决决策者(DMS)提供的评估信息以毕达哥兰犹豫不决的模糊数表示,以及有关属性权重的信息是 不完整。 确定属性权重,我们基于最大化偏差方法开发优化模型。 最后,我们提供了一个实际的决策问题,以证明所提出的方法的实施过程。

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