报告题目：Agentic Artificial Intelligence in Supply Chain Management - Optimization and Coordination
报告人：Stefan Minner教授
邀请人：徐照光 副教授
报告时间及地点：2026年3月9日9:00-10:30经济管理学院B305
报告人简况：
Stefan Minner is a Full Professor for Logistics and Supply Chain Management at the School of Management, Technical University of Munich (TUM) and a core-member of the Munich Data Science Institute (MDSI). Currently, he is Vice Dean of Research and Innovation at TUM School of Management. His research interests using methods of operations research, artificial intelligence and machine learning are in global supply chain design, transportation optimization and inventory management. His work was published in many peer reviewed journals, including Management Science, Manufacturing & Service Operations Management, Operations Research, Production and Operations Management, Transportation Science, Transportation Research Parts B, C and E, European Journal of Operational Research, and the International Journal of Production Research. For his research output, he is currently listed among the top 1% business professors in German speaking countries by Wirtschaftswoche and among the top 2% researchers worldwide in a citation-based ranking by Stanford University. He serves on several editorial boards of logistics and operations research journals. Currently, Stefan Minner is the Editor-in-Chief of the International Journal of Production Economics. Stefan Minner is a fellow of the International Society for Inventory Research (ISIR) and the International Foundation of Production Research (IFPR). He received the PhD supervisory award at TUM School of Management in 2024 and the Science Award for his lifetime achievements by the German Operations Research Society in 2025.
报告内容摘要：
The emergence of agentic AI provides new opportunities but also resembles old challenges in decentralized decision making in multi-agent supply networks. Distributed information and local decision making requires secure sharing of information and alignment of incentives. This poses challenges in particular under conflicting economic, risk, and sustainability criteria. The keynote reviews existing approaches and summarizes new opportunities and frameworks in distributed learning and agentic decision automation as well as aspects of human-AI interaction in this domain.
上一条：Publication of Production Economics Research in Peer-reviewed Journals: An Author’s, Editor’s, and Referee’s Perspective
下一条：应对碳中和的资源管理
【关闭】
