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PhD Defense Mr. J. Zhen, MSc

Title: Adjustable Robust Optimization. Theory, Algorithm and Applications
Supervisors: Prof. D. den Hertog, Prof. M. Sim

Adjustable robust optimization is a methodology to help decision makers make robust and resilient decisions that extend well into the future. In this thesis, we exploit Fourier-Motzkin elimination to investigate the theories and applications of adjustable robust optimization. As a result, a generic technique is developed to enhance the classical approximation scheme, and applied to several applications, e.g., medical appointment scheduling, lot-sizing on a network, wireless sensor networks, to demonstrate the efficiency and effectiveness of the proposed approach. We further show how to formulate two generic optimization problems, i.e., computing the maximum volume inscribed ellipsoid in a polytopic projection, and finding centered solutions for uncertain linear equations, as adjustable robust optimization problems, and investigate these two problems through the lens of Fourier-Motzkin elimination.

Jianzhe (Trevor) Zhen (Shandong, China, 1987) is a Postdoc at École Polytechnique Fédérale de Lausanne, Switzerland, since January 2018. This thesis was written when he was a PhD student at the Department of Econometrics and Operations Research at Tilburg University, where he also obtained his degrees in Econometrics and Operations Research (B.Sc.) and in Business with a specialization in Operations Research (M.Sc.). During his PhD, he has spent five and a half months at University of Singapore as a visiting scholar. He has won the Student Best Paper Prize at the Computational Management Science 2017 conference in Bergamo, Italy.



Location: Cobbenhagen building, Ruth First room (access via Koopmans building)


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When: 09 April 2018 16:00

Where: Route description Tilburg University campus