Tanmoy Mahapatra

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About

Tanmoy Mahapatra is a rising figure in applied fuzzy graph theory, whose work bridges abstract mathematical structures with real-world industrial optimization. His primary research areas include m-polar fuzzy graphs, inverse graph theory, and their applications in manufacturing and robotics. Mahapatra’s most notable contribution is the introduction and characterization of inverse graphs within m-polar fuzzy environments—a significant extension of classical crisp inverse graph concepts. By defining how nodes and edges with multiple (m) components interact through minimum relational constraints, he has opened new pathways for modeling complex, multi-attribute systems. His 2023 paper, cited 5 times, demonstrates the practical power of this theory by applying it to robotics manufacturing allocation problems, where resolvability techniques enable more efficient resource distribution. This work not only advances the theoretical foundations of fuzzy graph theory but also provides actionable algorithms for automation and logistics. Mahapatra’s research is particularly valuable for students and engineers seeking to apply fuzzy mathematical models to solve real-world allocation challenges, establishing him as an innovative voice at the intersection of pure graph theory and applied industrial engineering.