Fuzzy Mathematics in Decision-Making: A Quantitative Perspective

Year : 2025 | Volume : 12 | Issue : 01 | Page : 6 12
    By

    R chetana,

  • N. Raja,

  • Vasanthakumari T.N,

Abstract

Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates competing priorities. The fuzzy method’s comparison with standard deterministic and probabilistic risk models establishes them as more flexible and adaptive frameworks capable of reflecting real-world ambiguities. The fuzzy model is found especially accommodating in dealing with weighted priorities and imprecise data inputs. While computational complexity, calibration of membership functions, and the nuanced interpretation of results pose notable challenges, the multifaceted advantages of fuzzy mathematics are evident across domains such as finance, healthcare, environmental planning, and supply chain optimization. Furthermore, the integration of fuzzy logic with artificial intelligence and machine learning algorithms paves the way for intelligent decision support systems. These directions enable the advancement of hybrid models that combine the interpretability of fuzzy systems with the predictive power of data-driven techniques, enhancing usability and fostering broader adoption across industries.

Keywords: Fuzzy mathematics, decision-making, risk analysis, project management, aggregated risks, fuzzy logic, membership functions, computational complexity, hybrid models, artificial intelligence integration.

[This article belongs to Research & Reviews: Discrete Mathematical Structures ]

How to cite this article:
R chetana, N. Raja, Vasanthakumari T.N. Fuzzy Mathematics in Decision-Making: A Quantitative Perspective. Research & Reviews: Discrete Mathematical Structures. 2025; 12(01):6-12.
How to cite this URL:
R chetana, N. Raja, Vasanthakumari T.N. Fuzzy Mathematics in Decision-Making: A Quantitative Perspective. Research & Reviews: Discrete Mathematical Structures. 2025; 12(01):6-12. Available from: https://journals.stmjournals.com/rrdms/article=2025/view=207914


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Regular Issue Subscription Original Research
Volume 12
Issue 01
Received 14/01/2025
Accepted 13/02/2025
Published 15/04/2025
Publication Time 91 Days
230

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