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Novel approach to multi-attribute group decision-making based on interval-valued Pythagorean fuzzy power Maclaurin symmetric mean operator

机译:基于区间值毕达哥拉斯模糊功率Maclaurin对称均衡器的多属性组决策的新方法

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摘要

To distinguish any two interval-valued Pythagorean fuzzy numbers (IVPFNs), two new comparison functions, namely, the membership degree uncertainty (MU) function and the hesitation degree uncertainty (HU) function are proposed in this paper. By combining the existing score and accuracy functions with the proposed MU and HU functions, a new comparison rule for IVPFNs is obtained, whereby two different IVPFNs may be distinguished. Then, the interval-valued intuitionistic Pythagorean fuzzy power Maclaurin symmetric mean aggregation (IVPFPMSM) operator and the weighted IVIPFMSM aggregation operator are introduced to address complex multi-attribute group decision-making (MAGDM) problems involving unreasonable evaluation values and interaction among the input arguments. Moreover, a series of properties of the proposed operators are studied. Further, based on the proposed comparison method for IVPFNs and the weighted IVPFPMSM operator, we develop a new method for interval-valued Pythagorean fuzzy MAGDM problems. Finally, two illustrative examples and a comparative analysis are provided to demonstrate the effectiveness and superiority of the proposed method. Specifically, the advantage of the proposed operators in MAGDM problems is that they can eliminate bad influences of extreme evaluation values from biased decision makers and capture the interaction between attributes.
机译:为了区分任何两个间隔值的毕达哥兰模糊数(IVPFN),两个新的比较功能,即隶属度不确定性(MU)功能和犹豫不确定度(HU)功能。通过将现有的分数和准确性函数与所提出的MU和HU函数相结合,获得了IVPFN的新比较规则,从而可以区分两个不同的IVPFN。然后,引入了间隔值的直觉毕达哥拉斯模糊Maclaurin对称算法(IVPFPMSM)操作员和加权IVIPFMSM聚合运算符,以解决涉及不合理的评估值和输入参数之间的交互的复杂多属性组决策(MAGDM)问题。此外,研究了拟议的操作员的一系列性质。此外,基于所提出的IVPFN和加权IVPFPMSM运算符的比较方法,我们开发了一种新方法,用于区间值毕达哥兰模糊MAGDM问题。最后,提供了两个说明性实施例和比较分析以证明所提出的方法的有效性和优越性。具体地,所提出的操作员在MAGDM问题中的优点是它们可以消除对偏置决策者的极端评估值的不良影响,并捕获属性之间的互动。

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