Yun Ou

Papers

Total Citations

H-Index

About

Yun Ou is a researcher specializing in swarm intelligence algorithms and their engineering applications, with a particular focus on robot path planning and optimization. Their most-cited work, "An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning" (2023, 46 citations), introduces a novel hybrid algorithm—pGWO-CSA—that integrates a clone selection algorithm into the standard Grey Wolf Optimizer. This innovation addresses critical limitations of conventional GWO, including slow convergence, low accuracy in single-peak functions, and a tendency to become trapped in local optima for multi-peak problems. By enhancing exploration and exploitation capabilities, Ou's algorithm demonstrates significant improvements in solving complex, real-world optimization tasks, particularly in autonomous navigation. This contribution has been recognized as a valuable advancement in metaheuristic optimization, offering a robust tool for robotics and computational intelligence. Ou's work bridges theoretical algorithm design with practical deployment, making it a key reference for researchers seeking efficient, adaptive solutions in dynamic environments.