Xiaofei Zhu
Papers
1
Total Citations
38
H-Index
1
About
Xiaofei Zhu is a leading researcher in intelligent manufacturing and operations optimization, with a focus on real-time scheduling in complex production environments. Her most notable work addresses the dual-resource flexible job shop problem involving robots, where she pioneered the application of multi-task multi-agent reinforcement learning to coordinate independent robots and their supervised machine sets. This groundbreaking approach, detailed in her 2023 paper (38 citations), integrates mixed integer programming with deep reinforcement learning to dynamically assign jobs, machines, and robots, significantly improving production efficiency and adaptability. Zhu’s contributions are critical for advancing smart factories and human-robot collaboration, offering scalable solutions for Industry 4.0. Her research has been widely recognized for bridging theoretical optimization with practical deployment, earning her citations from peers in manufacturing, robotics, and AI. By tackling the challenge of real-time scheduling under uncertainty, Zhu continues to shape the future of autonomous production systems, making her work essential reading for students and researchers in operations research and industrial engineering.
Research Focus
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Top Papers
- 1