Xuan Xiong
Papers
1
Total Citations
3
H-Index
1
About
Xuan Xiong is a rising researcher in computational intelligence and optimization, whose work focuses on enhancing metaheuristic algorithms for real-world engineering applications. Their most-cited paper, “Q-learning-based exponential distribution optimizer with multi-strategy guidance for solving engineering design problems and robot path planning” (2025, 3 citations), addresses critical limitations in the Exponential Distribution Optimizer (EDO)—namely, its weak exploitation, poor exploration, and inflexible parameter switching. By integrating Q-learning reinforcement learning with multi-strategy guidance, Xiong significantly improves the algorithm’s adaptability and solution quality, demonstrating its effectiveness in complex engineering design tasks and autonomous robot path planning. This contribution not only advances the theoretical foundations of swarm intelligence but also provides practical tools for solving constrained optimization problems. Xiong’s work exemplifies a growing trend of hybridizing machine learning with nature-inspired algorithms to overcome traditional optimization bottlenecks. With a focus on bridging algorithmic innovation and engineering applicability, their research holds promise for fields ranging from robotics to industrial design, marking them as a notable emerging voice in the optimization community.
Research Focus
Key Achievements
Top Papers
- 1