Gourangajit Borah

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About

Gourangajit Borah is an emerging researcher specializing in fuzzy mathematics, decision-making under uncertainty, and multi-criteria decision analysis. His work focuses on advancing the theoretical foundations and practical applications of Generalized Fuzzy Numbers (GFNs), addressing longstanding limitations in how these mathematical constructs are manipulated and compared. Borah's most notable contribution lies in developing novel frameworks for working with GFNs in real-world decision-making contexts. His 2021 paper on robot selection using Fuzzy TOPSIS methodology introduced innovative distance and similarity measures specifically designed for GFNs with unequal heights — a technically demanding problem that classical approaches struggle to resolve effectively. This work, which has garnered 5 citations, demonstrates direct industrial relevance by helping multinational companies optimize robot selection processes, reducing reliance on human judgment in complex machinery procurement decisions. His 2024 study further strengthens this foundation by proposing a rigorous approach to arithmetic operations and ranking of GFNs, correcting irrational outputs that traditional methods frequently produce under uncertainty. With 3 citations already accumulated, this work signals growing recognition within the fuzzy systems community. Borah's research collectively advances both the mathematical rigor and applied utility of fuzzy decision-making tools, making him a promising contributor to intelligent systems and operations research.