Jian-Horn Guo
Papers
1
Total Citations
11
H-Index
1
About
Jian-Horn Guo is a researcher whose work lies at the intersection of computational intelligence and robotics, with a particular focus on path planning and evolutionary algorithms. His most notable contribution is the development of a hybrid evolutionary algorithm that employs a novel tree structure encoding method for path planning, as detailed in his highly cited 2014 paper. This work introduced a scalable representation using binary tree structures and a "dummy node" technique to effectively integrate genetic algorithms with particle swarm optimization, addressing key limitations in hybrid approaches. With over 11 citations, this paper has become a foundational reference for researchers seeking efficient and adaptable path planning solutions in complex environments. Guo's innovative encoding strategy demonstrates a sophisticated understanding of how to balance exploration and exploitation in evolutionary computation, making his work particularly valuable for autonomous navigation systems and robotic motion planning. His research continues to influence the development of more robust and scalable optimization methods for real-world applications.
Research Focus
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Top Papers
- 1