讲座题目 | Scalable Optimization for Integrated Supply Chains: Exact Decomposition and Learning-Assisted Methods | ||
主讲人 （单位） | Guoqing Zhang （温莎大学） | 主持人 （单位） | 李四杰、陈静 （东南大学） |
讲座时间 | 2026年4月16日上午10:30 April 16, 2026 at 10:30 AM | 讲座地点 | 经管楼B201 Room B201, School of Economics and Management |
主讲人简介 |
Guoqing Zhang, PhD, P.Eng., is a Professor of Industrial Engineering and Director of the Supply Chain and Logistics Optimization Research Center at the University of Windsor. His recent research interests include supply chain management and optimization, logistics, operations research, manufacturing modeling, algorithm design and development, machine learning, and intelligent decision support systems. He has published over 100 journal articles, and his research is continuously supported by NSERC. Dr. Zhang has developed a state-of-the-art solver for large-scale linear programming problems. Among his recognitions, he and his team won first place in the Canadian Operational Research Society’s Practice Prize competition in 2015. He currently serves as an Associate Editor for several leading journals. | ||
讲座内容摘要 | This talk addresses large-scale optimization in integrated supply chains, where increasing complexity challenges traditional solution methods. Two approaches are presented. First, an exact Benders decomposition framework is developed for an inventory sharing problem in perishable retail systems. Second, a learning-assisted metaheuristic approach integrates neural networks with genetic algorithms to solve a location–production–routing problem in distributed manufacturing. Together, these studies provide insights into scalable solution strategies for complex supply chain systems, with directions toward hybrid frameworks. | ||
