Affiliations: [a] School of Business, Sichuan Normal University, Chengdu, P.R. China | [b] China School of Finance, Southwestern University of Finance and Economics, Chengdu, P.R. China | [c] School of Accounting, Southwestern University of Finance and Economics, Chengdu, P.R. China
Correspondence:
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Corresponding author. Lu Xiao, School of Business, Sichuan Normal University, Chengdu, P.R. China.
E-mail: xl615732374@qq.com.
Abstract: 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, the Taxonomy 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.
Keywords: Multiple attribute group decision making (MAGDM), Interval-valued intuitionistic fuzzy sets, taxonomy method, entropy
