An improved IVHF-TOPSIS method based on hesitancy degree

Hong Cao

doi:10.1117/12.2691879

23 August 2023 An improved IVHF-TOPSIS method based on hesitancy degree

Hong Cao

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127842H (2023) https://doi.org/10.1117/12.2691879
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

In this paper, we propose a multi-attribute decision making method based on hesitancy degree. Firstly, it is found that there are some unreasonable situations in the existing hesitancy degree of interval-valued hesitant fuzzy set. Therefore, we define a new hesitancy degree function, which considers the number of elements, interval length and the element deviation degree. Then, the distance measure based on hesitancy degree is defined and its properties are proved. Secondly, when determining attribute weight, we introduce the proposed distance measure into the maximum deviation method to further improve the method of determining attribute weight. Therefore, an interval-valued hesitant fuzzy TOPSIS method is proposed by combining maximum deviation method and new distance measure. Finally, the feasibility and flexibility of the proposed method are verified by the investment problem, and the sensitivity and stability of the parameter is discussed.

Citation Download Citation

Hong Cao "An improved IVHF-TOPSIS method based on hesitancy degree", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127842H (23 August 2023); https://doi.org/10.1117/12.2691879

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