Papers
2
Total Citations
41
H-Index
2
About
M. Parimala is a leading researcher in the mathematical foundations of fuzzy decision-making, with a particular focus on linear Diophantine fuzzy (LDF) graph theory and soft set theory. Her work bridges abstract algebraic structures with practical optimization problems in wireless sensor networks and multi-criteria decision-making (MCDM). In her highly cited 2022 paper on “Lifetime prolongation of a wireless charging sensor network using a mobile robot,” Parimala introduced novel LDF graph concepts—including bridges, cut-vertices, and cycles—to model and extend network longevity, earning 23 citations. She further advanced the field by developing new MCDM algorithms, such as LDF soft TOPSIS and VIKOR, which integrate aggregation operators to handle linguistic uncertainty in real-world scenarios, a work cited 18 times. Her contributions provide a rigorous algebraic framework for tackling complex, ambiguous data, making her a pivotal figure in fuzzy mathematics. Parimala’s research not only deepens theoretical understanding but also offers actionable tools for engineers and computer scientists, demonstrating the power of fuzzy logic in edge networking and resource optimization.
Research Focus
Key Achievements
Top Papers
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