Automatic Construction Method of Surrogate Evaluation Measures for Job Shop Scheduling

Dr. Zigao Wu is a lecturer and deputy director of the Industrial Engineering Teaching and Research Section in the Department of Mechanical Engineering, School of Energy, Power and Mechanical Engineering, North China Electric Power University. He focuses on the fields of industrial engineering and intelligent manufacturing, and his main research areas include production operation and optimization, intelligent manufacturing systems, machine learning and intelligent optimization algorithms. He received his Bachelor of Science degree in Mechanical Design, Manufacturing and Automation from Harbin Institute of Technology in 2012, his Master of Science degree and Ph.D. in Mechatronics Engineering from Northwestern Polytechnical University in 2015 and 2020, respectively. In recent years, he has participated in the application and completion of 3 National Natural Science Foundation of China (NSFC) projects and 1 Shaanxi Provincial Key Research and Development Program project. He has published 6 academic papers in renowned domestic and international journals such as Computers & Operations Research and Journal of Mechanical Engineering, and has applied for/been granted 7 national invention patents.

Prof. Shichang Xiao is an associate professor and master’s supervisor at the College of Logistics Engineering, Shanghai Maritime University. He holds a PhD in Mechatronics Engineering from Northwestern Polytechnical University. He currently serves as the liaison for the Ministry of Education’s Virtual Teaching and Research Office for Practical Teaching in Industrial Engineering, the secretary of the university’s Master’s Degree Evaluation Committee for Logistics Engineering Management, and a founding member of the Research Sub-center for the Multimodal Transport Center of the Yangtze River Economic Belt. His main research areas are industrial engineering and logistics engineering, and he has achieved significant results in port scheduling optimization and intelligent manufacturing system modeling and scheduling optimization. He has led 5 major research projects and participated in 16 national, provincial, and industry-funded projects. He has published 20 academic papers, been granted 7 invention patents, and completed the commercialization of 2 patented technologies.

Dr. Shaohua Yu is a lecturer and master’s supervisor at the School of Intelligence Science and Technology, Nanjing University of Science and Technology. He holds a Bachelor of Engineering degree in Mechanical Design, Manufacturing and Automation from the School of Mechanical Engineering, Shandong University, a Master of Engineering and a Doctor of Engineering degree in Mechatronics Engineering from the Department of Industrial Engineering, School of Mechanical and Electrical Engineering, Northwestern Polytechnical University, and a Doctor of Philosophy degree in Computer Science and Technology from École Centrale Paris-Saclay University. His research interests include algorithm design driven by large language models/deep reinforcement learning, intelligent optimization algorithms and their applications, and operations research optimization algorithms and their applications. He serves as a reviewer for journals such as Transportation Research Part C: Emerging Technologies, Transportation Research Part E: Logistics and Transportation Review, Transportmetrica A: Transport Science, and Journal of Heuristics. He was a member of the program committee for the AICT 2021 and 2022 Technical Program Committee and a member of the 18th Wuxi Artificial Intelligence Industry Science and Technology Town Mayor Group.