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...

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Veröffentlicht in:Computer modeling in engineering & sciences Jg. 143; H. 1; S. 911 - 943
Hauptverfasser: Musa, Sagvan Y., Asaad, Baravan A., Alohali, Hanan, Ameen, Zanyar A., Alqahtani, Mesfer H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Henderson Tech Science Press 2025
Schlagworte:
Academic grading
Algorithms
Bipolarity
Computer science
Decision making
Fuzzy logic
Fuzzy sets
Mathematics
Multiple criteria decision making
Multiple criterion
Set theory
ISSN:1526-1506, 1526-1492, 1526-1506
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:1526-1506
1526-1492
1526-1506
DOI:10.32604/cmes.2025.062524