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ISyE Seminar Series


Online Resource Allocation Under Partially Predictable Demand

Wednesday, December 12
3:15pm - Refreshments, 3:30pm - Graduate Seminar
Lind Hall 305

 



Professor Patrick Jaillet

Department of Electrical Engineering and Computer Science

Massachusetts Institute of Technology

 

 


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.

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).

 

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