Papers
1
Total Citations
6
H-Index
1
About
Dewen Zeng is a researcher in computational intelligence and robotics, with a primary focus on optimization algorithms for path planning and navigation. His most-cited work, "An improved ant colony optimization algorithm based on dynamically adjusting ant number" (2012), addresses a critical limitation of traditional ant colony algorithms—premature convergence and failure to achieve global optimal solutions. By introducing a dynamic adjustment mechanism for ant populations, Zeng’s method enhances the algorithm’s ability to escape local optima, significantly improving performance in robot navigation and shortest-path problems. This contribution has garnered 6 citations, reflecting its relevance in the field of swarm intelligence and autonomous systems. Zeng’s research bridges theoretical algorithm design and practical robotics applications, offering more robust solutions for real-world path planning challenges. His work continues to influence studies on adaptive optimization techniques, making him a notable figure in the development of intelligent navigation systems.
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