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Speaker
Yinyu Ye
Professor of Management Science and Engineering
and, by courtesy, Electrical Engineering
Affiliation: Department of Management Science and Engineering
Stanford University
Abstract
A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) where the constraint matrix is revealed column by column along with the objective function. We provide a near-optimal algorithm for this surprisingly general class of online problems under the assumption of random order of arrival and some mild conditions on the size of the LP right-hand-side input. Our learning-based algorithm works by dynamically updating a threshold price vector at geometric time intervals, where the dual prices learned from revealed columns in the previous period are used to determine the sequential decisions in the current period. Our algorithm has a feature of learning by doing", and the prices are updated at a carefully chosen pace that is neither too fast nor too slow. In particular, our algorithm doesn't assume any distribution information on the input itself, thus is robust to data uncertainty and variations due to its dynamic learning capability. Applications of our algorithm include many online multi-resource allocation and multi-product revenue management problems such as online routing and packing, online combinatorial auctions, adwords matching, inventory control and yield management.
This is a joint work with Shipra Agrawal and Zizhuo Wang.
Bio
Yinyu Ye received the B.S. degree in System Engineering from the Huazhong University of Science and Technology, Wuhan, China, and the M.S. and Ph.D. degrees in Management Science & Engineering from Stanford University, Stanford. Currently, he is a full Professor of Management Science and Engineering and Institute of Computational and Mathematical Engineering and the Director of the MS&E Industrial Affiliates Program, Stanford University. His current research interests include Continuous and Discrete Optimization, Mathematical Programming, Algorithm Design and Analysis, Computational Game/Market Equilibrium, Metric Distance Geometry, Graph Realization, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc.
The following is a list of some of his main achievements:
