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Chethana N S,
- Research Student, Department of Mathematics, Central University of Karnataka, Aland Road, Kalaburagi, Andhra Pradesh, India
Abstract
Fuzzy mathematics play an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and it signs other possible solutions in addition to fuzzy mathematics. Fuzzy models offer a versatile and precise approach to assessing complex situations through the use of fuzzy sets, membership functions, and aggregation methods. Through time, cost and quality, the project management case study illustrates how fuzzy logic works for them. The fuzzy method’s comparison with standard risk models defines them more flexible and accurate models. The fuzzy model is found flexible in terms of dealing with weighted priorities. While computational complexity and the interpretation of results are some challenges faced by the researchers, the benefits of fuzzy mathematics in finance, healthcare, and supply chain management among many domains make it an important tool still. These directions are the establishment of AI and requirements of machine learning in fuzzy system and usability of fuzzy tools for more general use.
Keywords: Fuzzy Mathematics, Decision-Making, Risk Analysis, Project Management, Aggregated Risks, Fuzzy Logic, Membership Functions, Computational Complexity, Hybrid Models, Artificial Intelligence Integration
Chethana N S. A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments. Research & Reviews: Discrete Mathematical Structures. 2026; 13(01):-.
Chethana N S. A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments. Research & Reviews: Discrete Mathematical Structures. 2026; 13(01):-. Available from: https://journals.stmjournals.com/rrdms/article=2026/view=236562
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Research & Reviews: Discrete Mathematical Structures
| Volume | 13 |
| 01 | |
| Received | 21/01/2026 |
| Accepted | 28/01/2026 |
| Published | 05/02/2026 |
| Publication Time | 15 Days |
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