Xiuxi Wei
Papers
1
Total Citations
9
H-Index
1
About
Xiuxi Wei is a rising researcher in computational intelligence and robotics, whose work focuses on solving complex optimization problems through novel metaheuristic algorithms. Their primary research areas include swarm intelligence, differential evolution, and multi-robot path planning—a notoriously challenging NP-hard problem that demands efficient coordination and collision-free navigation. Wei’s most notable contribution is the development of a self-adaptive differential evolution-based coati optimization algorithm, which intelligently integrates two differential evolution strategies to enhance the exploration and exploitation capabilities of the standard coati optimization algorithm. This innovation has been successfully applied to multi-robot path planning, demonstrating significant improvements in solution quality and convergence speed. With their 2025 paper already garnering 9 citations, Wei’s work is gaining traction for its practical relevance in autonomous systems and logistics. By bridging the gap between nature-inspired algorithms and real-world robotic applications, Xiuxi Wei is establishing a reputation for advancing adaptive optimization techniques that can dynamically respond to complex, multi-agent environments.
Research Focus
Key Achievements
Top Papers
- 1