Liya Yu
Papers
1
Total Citations
3
H-Index
1
About
Liya Yu is a researcher whose work focuses on advancing metaheuristic optimization algorithms and their real-world applications. Her key research areas include swarm intelligence, evolutionary computation, and engineering optimization. Yu’s major contribution lies in the development of a Q-learning-based Exponential Distribution Optimizer (EDO) with multi-strategy guidance, which addresses critical limitations in standard EDO—namely, insufficient exploitation, poor exploration, and weak parameter adaptability. This hybrid approach integrates reinforcement learning to dynamically balance exploration and exploitation, significantly enhancing optimization performance. Her work has been applied to complex engineering design problems and robot path planning, demonstrating practical impact. With her most-cited paper already garnering 3 citations shortly after publication in 2025, Yu’s research is gaining traction in the optimization community. Her innovative fusion of learning-based strategies with mathematical optimization techniques marks a notable achievement, offering a robust framework for solving challenging real-world problems.
Research Focus
Key Achievements
Top Papers
- 1