Xiaoyu Wen
Papers
1
Total Citations
4
H-Index
1
About
Xiaoyu Wen is a rising researcher in industrial engineering and optimization, whose work focuses on the intersection of artificial intelligence and sustainable manufacturing. Wen’s primary research areas include multi-objective optimization, metaheuristic algorithms, and energy-efficient production systems. Their most notable contribution is the development of an improved multi-objective harmony search algorithm that integrates reinforcement learning—a novel approach that dynamically adapts search strategies to solve complex, real-world problems. This work, published in 2025, has already garnered 4 citations, signaling early impact in the field. Wen’s research directly addresses the critical challenge of balancing automated assembly line efficiency with energy consumption, offering practical solutions for greener manufacturing. By combining reinforcement learning with traditional harmony search, Wen has demonstrated a new pathway for creating adaptive, intelligent optimization tools. As a researcher committed to advancing both algorithmic theory and industrial application, Wen’s work is poised to influence future studies in sustainable production and smart automation. Their innovative methodology and focus on pressing environmental issues mark them as a promising voice in modern engineering optimization.
Research Focus
Key Achievements
Top Papers
- 1