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An Extended Taxonomy Method Based on Normal T-Spherical Fuzzy Numbers for Multiple-Attribute Decision-Making

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Abstract

T-spherical fuzzy set (T-SFS) is suitable for the situation where human opinions are not limited to yes or no, but include abstinence and refusal, and can be viewed as a generalization of fuzzy set (FS), intuitionistic FS and picture FS. Normal fuzzy number (NFN) is a useful tool to character phenomenon with normal distribution. Based on the advantages of T-SFS and NFN, we first propose the normal T-spherical fuzzy numbers (NT-SFNs) which can depict both normal distribution phenomenon and neutral information with a considerably large expression domain. Then, we define the operational laws, score function, accuracy function, expectation as well as distance measure of NT-SFNs. To deal with multiple-attribute decision-making (MADM) problems with NT-SFNs and unknown weights of attributes, we use the best worst method (BWM) to obtain the subjective weights, the criteria importance through intercriteria correlation (CRITIC) method to obtain the objective weights, and the minimum total deviation method to calculate the combination weights of attributes. Then, the Taxonomy method is used to rank the alternatives and the normal T-spherical fuzzy Taxonomy (NTSF-Taxonomy) method is proposed. Finally, two numerical examples and comparative analysis are conducted to verify the validity of the NTSF-Taxonomy method.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (No. 71771140), Project of cultural masters and “the four kinds of a batch” talents, the Special Funds of Taishan Scholars Project of Shandong Province (No. ts201511045), Major bidding projects of National Social Science Fund of China (No. 19ZDA080).

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  1. School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, 250014, Shandong, China

    Peide Liu & Dongyang Wang

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  1. Peide Liu
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Correspondence to Peide Liu.

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Liu, P., Wang, D. An Extended Taxonomy Method Based on Normal T-Spherical Fuzzy Numbers for Multiple-Attribute Decision-Making. Int. J. Fuzzy Syst. 24, 73–90 (2022). https://doi.org/10.1007/s40815-021-01109-7

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