Papers
3
Total Citations
103
H-Index
3
About
Slim Daoud is a leading researcher in industrial robotics and manufacturing optimization, with a focus on robotic assembly line balancing and pick-and-place system efficiency. His work bridges mathematical modeling and metaheuristic algorithms to solve complex real-world automation challenges. Daoud’s most influential contributions include developing efficient hybrid methods that significantly improve robotic system performance, as evidenced by his highly cited papers: “Efficient metaheuristics for pick and place robotic systems optimization” (49 citations) and “Solving a robotic assembly line balancing problem using efficient hybrid methods” (48 citations). He also introduced a novel mathematical model for robotic assembly lines, published in 2012, which provides a rigorous foundation for balancing tasks in automated production. Daoud’s research has practical implications for industries seeking to enhance productivity and reduce costs through smarter robotics. His work is particularly notable for combining theoretical rigor with actionable solutions, making him a key figure in advancing the field of robotic manufacturing optimization.
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