Yu Guodong

Professor Yu Guodong is a faculty member in the Department of Project Management and Industrial Engineering at Shandong University's School of Management. He holds the title of Qilu Young Scholar and leads an excellent young innovation team. His research focuses on data-driven decision optimization, particularly in small data environments, with applications in supply chain management, emergency response, and industrial systems. He has pioneered methods like Wasserstein distributionally robust optimization and fairness-aware resource allocation frameworks. His work addresses challenges in high-end manufacturing, emergency logistics, and low-probability event scenarios.

Yu has published extensively in top-tier journals including Manufacturing & Service Operations Management, Production and Operations Management, and INFORMS Journal on Computing. He has secured 12 national and provincial grants, including key projects from the National Natural Science Foundation of China. Collaborations with industry leaders like Weichai Power and Jereh Petroleum Equipment demonstrate his applied research impact. His team develops computationally efficient algorithms (e.g., Benders decomposition, Branch-and-Benders-cut) to solve complex optimization problems under uncertainty.

Notable contributions include integrating inverse optimization with historical data for contract pricing, quantifying fairness-efficiency trade-offs via robust optimization, and designing resilient service networks for emergencies. His research bridges theoretical advancements and practical implementation, enhancing decision-making resilience in data-scarce scenarios.