Papers
3
Total Citations
103
H-Index
3
About
Lionel Amodeo is a leading researcher in the optimization of robotic and manufacturing systems, with a primary focus on metaheuristics and hybrid methods for complex industrial problems. His work centers on the efficient design and balancing of robotic assembly lines, where he has developed novel mathematical models and solution approaches that significantly improve productivity and resource allocation. Notably, his 2012 paper on "Efficient metaheuristics for pick and place robotic systems optimization" has garnered 49 citations, establishing a foundation for advanced robotic path planning. His 2014 study on "Solving a robotic assembly line balancing problem using efficient hybrid methods" (48 citations) further demonstrates his impact, introducing hybrid algorithms that outperform traditional techniques. Amodeo's contributions are critical for industries seeking to automate and optimize pick-and-place operations and assembly line configurations, bridging the gap between theoretical optimization and practical robotic implementation. His work is widely recognized for its applicability in manufacturing engineering, making him a key figure in the advancement of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Efficient metaheuristics for pick and place robotic systems optimization49 citations · 2012
- 2
- 3New mathematical model to solve robotic assembly lines balancing6 citations · 2012