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Modeling of Decision-Making Based on Hesitant Fuzzy Sets

Author

Listed:
  • Muhammad Sarwar Sindhu

    (Department of Mathematics, Virtual University of Pakistan)

  • Muhammad Ahsan

    (Department of Mathematics, Virtual University of Pakistan)

  • Khalil Ahmad

    (Department of Physics, Virtual University of Pakistan)

  • Imran Ameen Khan

    (Department of Management Sciences, Virtual University of Pakistan)

Abstract

The hesitant fuzzy set (HFS) is successfully used as a fuzzy set (FS) extension to demonstrate circumstances where it is permissible to determine a few potential membership de- grees (MDs) of a component in a set due to the uncertainty between distinct values. Aggregation operators (AOs) are widely applied to accumulate vague and uncertain information these days. The hesitant fuzzy weighted aggregation geometric (HFWAG) operator is created by the authors as a new AO for hesitant fuzzy (HF) data. Some of the most important qualities of the suggested operators are highlighted, as well as their extensive interrelationship. Then, using those operators, we develop a methodology for interpreting the HF multiple criteria decision making (MCDM) hurdles. The proposed concepts are demonstrated using a real-life example related to medical di- agnosis, with the results’ believability tested using test criteria and compared. Because the weights of criteria can affect the outcome of a choice, they have a substantial impact on judgments. The De Luca-Termini entropy metric is utilized to estimate the weights of criteria in the current work. Moreover, TOPSIS and VIKOR were also employed to compare the results of our method.

Suggested Citation

  • Muhammad Sarwar Sindhu & Muhammad Ahsan & Khalil Ahmad & Imran Ameen Khan, 2024. "Modeling of Decision-Making Based on Hesitant Fuzzy Sets," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(1), pages 720-729.
    • Handle: RePEc:rfh:bbejor:v:13:y:2024:i:1:p:720-729
    DOI: https://doi.org/10.61506/
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    References listed on IDEAS

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    2. Kannan, Devika & Jabbour, Ana Beatriz Lopes de Sousa & Jabbour, Charbel José Chiappetta, 2014. "Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company," European Journal of Operational Research, Elsevier, vol. 233(2), pages 432-447.
    3. Bin Zhu & Zeshui Xu & Meimei Xia, 2012. "Dual Hesitant Fuzzy Sets," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-13, May.
    4. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang & Chen-Ming Lu, 2021. "A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
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