Lyes Tighzert
Papers
9
Total Citations
94
H-Index
5
About
Lyes Tighzert is a researcher at the forefront of computational intelligence, specializing in the development of compact swarm intelligence algorithms and their application to robotics and autonomous systems. His most significant contribution is the introduction of a new class of memory-efficient optimization techniques, including the compact firefly optimizer (cFO) and compact harmony search algorithm (cSA), which dramatically reduce computational cost and memory storage while maintaining high performance. His seminal work, "A set of new compact firefly algorithms" (2017), has garnered 56 citations, establishing a foundation for resource-constrained optimization. Tighzert’s research extends to practical robotics applications, where he has pioneered intelligent trajectory planning and control for humanoid and flying robots. Notable achievements include developing algorithms for bipedal robot walking, self-standing of humanoid robots, and gymnastic movement realization on bars. His recent work on nature-inspired trajectory planning for inspection flying robots in smart grids (2024) demonstrates the real-world impact of his algorithms in critical infrastructure. With over 90 total citations, Tighzert’s compact swarm intelligence paradigm offers a powerful solution for embedded systems and real-time robotic control, bridging the gap between theoretical optimization and practical deployment.
Research Focus
Key Achievements
Top Papers
- 1A set of new compact firefly algorithms56 citations · 2017
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- 3Self-stunding up of humanoid robot using a new intelligent algorithm7 citations · 2016
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- 6Flying Robot Trajectory Tracking Through Metaheuristic-Based Control3 citations · 2024
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- 8Rate learning-based fish school search algorithm for global optimization3 citations · 2017
- 9