Data-driven Optimization: Modeling and Applications in Management
发布人: 系统管理员   发布时间: 2015-11-18   浏览次数: 74

1122Data-driven Optimization: Modeling and Applications in Management


讲座题目:Data-driven Optimization: Modeling and Applications in Management

主讲人:Yinyu Ye教授

主持人:羊丹平 教授



主办单位:数学系 科技处

报告人简介:Yinyu Ye is the K.T. Li Chair Professor of Engineering at Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering, Stanford University and the Director of the MS&E Industrial Affiliates Program.

His research interests include Data Science and Application, Continuous and Discrete Optimization, Algorithm Design and Analysis, Computational Game/Market Equilibrium, Metric Distance Geometry, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc.

He is an INFORMS (The Institute for Operations Research and The Management Science) Fellow since 2012, and has received several academic awards including the winner of the 2014 SIAM Optimization Prize, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2006 Farkas Prize on Optimization, the 2009 IBM Faculty Award, etc. He is the Chief Scientist of one of the major commercial international optimization software companies. His text book written with David Luenberger, “Linear and Nonlinear Programming,” has been popularly used in academic education. Ye demonstrated his leadership in managing a group of researchers on a broader range of government and industrial projects including Boeing, American Express, Oracle, and IBM, focusing on big data, business analytics, sensor network, risk management, electronic commerce, Internet economics, etc., he also manages a broader range of government and industry funded research projects.

He received the B.S. in System Engineering from the Huazhong University of Science and Technology, China, and the M.S. and Ph.D. in Engineering-Economic Systems and Operations Research from Stanford University.


In this talk we discuss some data-driven optimization problems with emerging demands from big-data era that call for different formulations, models, analytical approaches and implementations from traditional models. We also introduce a few interesting business cases which are drawn from industries such as logistics, supply chain management, inventory control, revenue management, risk management, and etc. The power and limitation of the optimization methods in data industry will be fully exhibited.

Joint work with Dongdong Ge(Shanghai University of Finance and Economics).