Yuhao Fu
Papers
1
Total Citations
2
H-Index
1
About
Yuhao Fu is a researcher whose work lies at the intersection of automation, artificial intelligence, and manufacturing systems engineering. His primary research focus is on the intelligent scheduling of flexible manufacturing systems (FMS), where he has pioneered novel approaches that combine Petri net modeling with advanced search algorithms. In his most cited work, Fu developed a groundbreaking method that integrates A* search with a neural network heuristic function to optimize production schedules in complex manufacturing environments. This approach is notable for its ability to calculate minimal production times for each system state using place-timed Petri nets, significantly improving efficiency in automated production lines. While his citation count is still growing, Fu's contributions represent an important step toward more adaptive and intelligent manufacturing systems. His work demonstrates how deep learning techniques can enhance traditional scheduling algorithms, offering practical solutions for reducing production bottlenecks and improving throughput in modern factories. For students and researchers in industrial engineering and AI, Fu's research provides a compelling example of how neural networks can be leveraged to solve complex optimization problems in real-world manufacturing contexts.
Research Focus
Key Achievements
Top Papers
- 1