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Complex intuitionistic fuzzy ordered weighted distance measure

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Abstract

Compared with the complex fuzzy set (CFS) and the intuitionistic fuzzy set (IFS), the complex intuitionistic fuzzy set (CIFS) can handle the two-dimensional and uncertain information simultaneously, and thus strengthen the capability of capturing useful information. In this paper, we consider the situation with complex intuitionistic fuzzy environment, where the importance of certain information is also taken into consideration. To deal with these situations, we develop the complex intuitionistic fuzzy ordered weighted distance (CIFOWD) measure and investigate its main properties. We find that the CIFOWD measure provides a parameterized family of aggregation distance measures, which includes, for example, complex intuitionistic fuzzy ordered weighted geometric distance (CIFOWGD) measure, complex intuitionistic fuzzy ordered weighted Hamming distance (CIFOWHD) measure, and complex intuitionistic fuzzy ordered weighted Euclidean distance (CIFOWED) measure as special types. The CIFOWD measure is capable of alleviating the influence of excessively large or excessively small deviations on the aggregation results via weight vector. Based on these distance measures, a multiple criteria group decision-making approach is presented under the CIFSs environment. An illustrative example regarding coronavirus vaccine selection on COVID-19 is taken for demonstrating the effectiveness of the proposed approach. Finally, the proposed results are compared with the results obtained from the existing methods.

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Acknowledgements

This work was supported by the Science and Technology Major Program of Sichuan (No.2020YFG0290), the Natural Science Foundation of Guangxi (No.2019GXNSFAA185033), and the National Natural Science Foundation of China (No.62172075).

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Authors and Affiliations

  1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Kaiyan Yang & Lan Shu

  2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Guowu Yang

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  1. Kaiyan Yang
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Correspondence to Kaiyan Yang.

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Communicated by Zdenko Takac.

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Yang, K., Shu, L. & Yang, G. Complex intuitionistic fuzzy ordered weighted distance measure. Comp. Appl. Math. 41, 353 (2022). https://doi.org/10.1007/s40314-022-02061-4

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