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Dr.Yuli Zhang's Lecture Notice

Publish Date: 2017/09/22 09:20:59    Hits:

Topic:Distributionally Robust Optimization and its Applications

Lecturer:Dr.Yuli Zhang, Tsinghua University

Time:2017.9.27,16:00-17:30

Location:New Main BuildingA716

Lecturer:

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-driven 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.

Abstract:

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.

School of Economics & Management

2017-09-22