ISyE Seminar Series: Patrick Jaillet
"Online Resource Allocation under Partially Predictable Demand"Presentation by Professor Patrick Jaillet Wednesday, December 12
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About: There are many situations in which present actions must be made and resources allocated with incomplete knowledge of the future. Online optimization typically compares the performance of a strategy that operates with no knowledge of the future (on-line) with the performance of an optimal strategy that has complete knowledge of the future (off-line). In some cases, partial information about the future may be learnable and lead to provably better online algorithms. In this talk, we provide recent results obtained from that perspective on a simple online resource allocation problem where the sequence of arrivals (requests) contains both an adversarial component and a stochastic one.
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Bio: Patrick Jaillet is the Dugald C. Jackson Professor in the Department of Electrical Engineering and Computer Science and a member of the Laboratory for Information and Decision Systems at MIT. He is also co-Director of the MIT Operations Research Center and the Faculty Director of the MIT-France Program. Dr. Jaillet's research interests include online optimization and learning; real-time, dynamic, and data-driven problems; and networks. He is a Fellow of the Institute for Operations Research and Management Science Society (INFORMS) and a member of the Society for Industrial and Applied Mathematics (SIAM). |