Papers

7

Total Citations

199

H-Index

5

About

Nachol Chaiyaratana is a computational intelligence researcher whose work sits at the intersection of evolutionary computation, neural networks, and robotic control systems. He is perhaps best known for his early and influential review of genetic algorithm theory and applications, published in 1997, which has garnered 126 citations and remains a key reference for researchers entering the field. This foundational work surveyed advances in genetic operators, niching techniques, and algorithmic design, helping to consolidate a rapidly evolving discipline. Chaiyaratana's subsequent research pushed these theoretical insights into practical robotics, exploring how neural networks and genetic algorithms can be hybridised to solve complex real-world control problems. His investigations into time-optimal path planning for robotic systems, friction compensation, and closed-loop control demonstrate a sustained effort to bridge intelligent optimization with precision engineering. Notably, he developed a multi-objective diversity control oriented genetic algorithm (MODCGA), extending multi-objective evolutionary methods to tackle challenging trajectory planning tasks. Later work on biped robot gait optimization further illustrates his commitment to applying evolutionary multi-objective techniques to embodied systems. Across his career, Chaiyaratana has contributed meaningfully to both the theoretical foundations and applied frontiers of neuro-evolutionary computation.

Research Focus

Key Achievements

5
H-Index
7
Papers
199
Total Citations
28
Avg Citations/Paper
🏆 Most Cited Paper
Recent developments in evolutionary and genetic algorithms: theory and applications
126 citations · 1997
📈 Most Prolific Year: 2002 (3 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Sheffield, King Mongkut's University of Technology North Bangkok

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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