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清华大学张玉利博士讲座通知

发布时间: 2017/09/22 09:18:34     点击次数:次   打印本页

【北航经管学术论坛】

清华大学张玉利博士讲座通知

 

题目:Distributionally Robust Optimization and its Applications

主讲人:Yuli Zhang

张玉利博士,清华大学工业工程系)

时间:2017927日(周三)下午16:00-17:30

地点:新主楼A716

邀请人:田琼教授

主讲人介绍:

Dr.Yuli Zhang received his M.S., and Ph.D. degrees from the Department of Automation, Tsinghua University in 2014. He visited the Department of IE&OR, University of California, Berkeley, during 2011- 2012.Currently he is a Postdoc Research Fellow in Department of Industrial Engineering, Tsinghua University. His research interest focuses on data-drive operations management. His work has been published in journals, such as Production and Operations Management, Transportation Research Part B, European Journal of Operational Research, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Systems, Man, and Cybernetics. His work is supported by the National Natural Science Foundation of China and Postdoctoral Science Foundation of China.

摘要:

Uncertainty is an inevitable element in real-world systems and has a significant impact on the system performance. In the last decades,robust optimization approaches has been adopted as a powerful tool to model uncertain parameters with inexact distributions and seek optimal robust decisions. In this talk, I will first discuss how to handle uncertaindemands in multi-period inventory management and uncertain travel times in intelligent transportation systems by proposing novel distributionally robust optimization models. We explicitly characterize the impact of mean-covariance information of uncertain factors on system performance and deliver interesting managerial insights. Then, I will introduce our newly proposed parametric search algorithm, which provides an exact and flexible solution framework for distributionally robust optimization models with orders of magnitude speedup over state-of-the-art algorithms. Finally, I will discuss how to establish data-driven models by integrating machine learning with robust optimization.

经管学院科研办

2017-09-22