报告题目：Reimagining Production and Operations Management via Artificial Intelligence
报 告 人：彭一杰 南京大学
报告时间：2026年9月22日（星期二）下午15:00
报告地点：经管学院C301会议室
个人简介：
彭一杰，南京大学至诚特聘教授，工程管理学院、计算机学院、先进制造学院博导，复杂系统管理研究院院长、智能系统管理系主任；北京大学信息技术高等研究院多智能体与工业智能实验室主任。主要研究方向包括人工智能、仿真建模与优化、智能制造、金融工程与风险管理等。主持国家自然科学基金优秀青年科学基金、原创探索计划、杰出青年科学基金等课题。在《Journal of Machine Learning Research》、《Operations Research》、《INFORMS Journal on Computing》、《IEEE Transactions on Automatic Control》等权威期刊与人工智能顶会上发表多篇高水平学术论文；曾获INFORMS Outstanding Simulation Publication Award、教育部第九届高等学校科学研究优秀成果二等奖、冬季仿真大会（WSC）优秀论文奖、IEEE自动化与机器人大会优秀论文奖等。担任或曾担任Journal of System Science and Engineering、《系统管理学报》领域主编，Asia-Pacific Journal of Operational Research、Journal of Systems Science and Information、Data Research and Applications、《运筹学报》、《管理科学》副主编，北京运筹学会副理事长、管理科学与工程协会人工智能技术与管理应用分会副理事长、管理科学与工程协会理事。
报告简介：Amid industrial digitalization, artificial intelligence redefines the collaborative optimization logic of production and operations management. We identify the core industrial dilemma: fragmented departmental decisions create local optima while sacrificing global efficiency across procurement, inventory, production, workshop execution and sales links. We address a comprehensive set of synergistic decision tasks, including large-scale multi-echelon inventory management, joint inventory-pricing/recommendation optimization, integrated production scheduling, new-product demand forecasting, and cross-domain production-logistics-sales coordination. To resolve such complex combinatorial problems, he develops dedicated AI tools ranging from deep reinforcement learning and Monte Carlo Tree Search-based mixed-integer programming to collaborative decision foundation models and industrial management world models. Verified via manufacturing and retail real-world datasets, these AI frameworks break functional silos, cut inventory and production costs, and boost overall supply chain performance. This presentation summarizes practical managerial guidelines and maps out future research frontiers for intelligent end-to-end industrial coordination.
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西北农林科技大学
经济管理学院
