Gajanan Waghmare
Papers
3
Total Citations
246
H-Index
2
About
Gajanan Waghmare is a researcher whose work lies at the intersection of optimization algorithms and mechanical design, with a particular focus on robotics. His major contributions center on applying and advancing metaheuristic optimization techniques—most notably the Teaching-Learning-Based Optimization (TLBO) algorithm and the parameter-free Jaya algorithm—to solve complex, real-world engineering problems. Waghmare’s most influential work, "A new optimization algorithm for solving complex constrained design optimization problems" (2016), has garnered 207 citations, highlighting its significance in demonstrating the Jaya algorithm’s effectiveness without the burden of tuning algorithm-specific control parameters. He has further applied these methods to practical robotics challenges, such as optimizing the geometrical dimensions of robot grippers (37 citations) and achieving optimum static balancing of robot manipulators. His research bridges the gap between theoretical algorithm development and tangible engineering applications, offering efficient solutions for constrained design problems. Waghmare’s work is particularly valuable for students and researchers in mechanical and robotics engineering, as it provides accessible, parameter-free optimization tools that simplify complex design processes while delivering robust performance.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Optimum static balancing of a robot manipulator using TLBO algorithm2 citations · 2018