Fuzzy N-Bipolar Soft Sets for Multi-Criteria Decision-Making: Theory and Application
This paper introduces fuzzy N-bipolar soft (FN-BS) sets, a novel mathematical framework designed to enhance multi-criteria decision-making (MCDM) processes under uncertainty. The study addresses a significant limitation in existing models by unifying fuzzy logic, the consideration of bipolarity, and the ability to evaluate attributes on a multinary scale. The specific contributions of the FN-BS framework include: (1) a formal definition and set-theoretic foundation, (2) the development of two innovative algorithms for solving decision-making (DM) problems, and (3) a comparative analysis demonstrating its superiority over established models. The proposed framework is applied to a real-world case study on selecting vaccination programs across multiple countries, showcasing consistent DM outcomes and exceptional adaptability to complex and uncertain scenarios. These results position FN-BS sets as a versatile and powerful tool for addressing dynamic DM challenges.
Authors
- Baravan A. Asaad (ORCID: https://orcid.org/0000-0002-2049-2044)
- Zanyar A. Ameen (ORCID: https://orcid.org/0000-0003-0740-3331)
- Mesfer H. Alqahtani (ORCID: https://orcid.org/0000-0002-8097-9057)
- Sagvan Y. Musa (ORCID: https://orcid.org/0000-0002-3923-2277)
- Hanan Alohali (ORCID: https://orcid.org/0009-0005-0052-4976)
Publication Details
- Journal
- Computer Modeling in Engineering & Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/cmes.2025.062524
- Citations
- 3
- Primary Topic
- Fuzzy and Soft Set Theory
- Type
- article
- Field-Weighted Citation Impact
- 6.32