Papers
1
Total Citations
2
H-Index
1
About
Chunming Gao is a leading researcher in operations management and industrial engineering, with a primary focus on job-shop scheduling and resource flexibility. His work bridges traditional optimization methods with cutting-edge artificial intelligence, offering transformative approaches to complex manufacturing and logistics challenges. Gao’s most-cited paper, "Job-shop scheduling with resource flexibility: A systematic review from traditional to AI-integrated approaches" (2026), has already garnered 2 citations, signaling early impact in a rapidly evolving field. This comprehensive review synthesizes decades of research, mapping the transition from heuristic and mathematical programming techniques to AI-driven solutions like machine learning and reinforcement learning. By identifying critical gaps and future directions, Gao provides a foundational roadmap for researchers and practitioners aiming to enhance production efficiency and adaptability. His contributions are particularly notable for integrating resource flexibility—a key enabler of resilient and responsive systems—into scheduling frameworks. Gao’s work is essential reading for students and scholars seeking to understand the state of the art in intelligent manufacturing, and his systematic approach promises to shape the next generation of scheduling algorithms.
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