Zhi‐Hui Zhan
Papers
4
Total Citations
269
H-Index
4
About
Zhi-Hui Zhan is a leading figure in computational intelligence, whose research bridges evolutionary optimization, multi-robot systems, and autonomous navigation. His most influential work introduces a meta-knowledge transfer-based differential evolution for multitask optimization, a paradigm-shifting approach that enables different optimization tasks to share high-level solution strategies rather than just raw solutions—garnering 177 citations and establishing a new direction in multitask evolutionary algorithms. In multi-robot task allocation, Zhan has developed strength learning particle swarm optimization and an efficient ant colony system that handle large-scale cooperative tasks with precedence constraints, addressing the critical challenge of coordinating heterogeneous robots in complex missions. His work on intelligent path planning for autonomous underwater vehicles (AUVs) using an estimation of distribution algorithm (EDA) with a learning fixed height histogram approach has advanced real-time navigation in dynamic underwater environments. With over 55 citations on his multirobot scheduling work alone, Zhan’s contributions are shaping how autonomous systems learn, transfer knowledge, and collaborate—making him a key innovator at the intersection of evolutionary computation and robotics.
Research Focus
Key Achievements
Top Papers
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