Interval-valued intuitionistic fuzzy set (IVIFS) is a flexible method to deal with uncertainty and fuzziness. For the past few years, extensive researches about the multi-attribute group decision making (MAGDM) problems based on IVIFSs has been extensively studied in many fields. In this study, theTaxonomy method based on IVIFSs (IVIF-Taxonomy) was proposed for MAGDM problems. For the sake of the objectivity of attribute weight, entropy is introduced into the proposed model. The IVIF-Taxonomy method fully considers the weight of the decision makers (DMs) and the homogeneity of the chosen alternatives, making it more realistic. In addition, we apply IVIF-Taxonomy method to fund selection to verify the validity of IVIF-Taxonomy method. Finally, the trustworthy of IVIF-Taxonomy method is proved by comparing with the aggregate operator, IVIF-TOPSIS method, IVIF-GRA method and modified IVIF-WASPAS method.

中文翻译：

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基于带熵的区间直觉模糊的多属性群决策分类方法

区间值直觉模糊集（IVIFS）是一种处理不确定性和模糊性的灵活方法。在过去的几年里，基于 IVIFS 的多属性群决策（MAGDM）问题的广泛研究在许多领域得到了广泛的研究。本研究针对MAGDM问题提出了基于IVIFSs的Taxonomy方法（IVIF-Taxonomy）。为了属性权重的客观性，在所提出的模型中引入了熵。IVIF-Taxonomy 方法充分考虑了决策者（DMs）的权重和所选择的替代方案的同质性，使其更加现实。此外，我们将IVIF-Taxonomy方法应用于基金选择，以验证IVIF-Taxonomy方法的有效性。最后，通过与聚合算子的比较，证明了IVIF-Taxonomy方法的可信度，