Near-Optimal Online Algorithms for Dynamic Resource Allocation Problems
Data Structures and Algorithms
2015-03-20 v1 Computer Science and Game Theory
Abstract
In this paper, we study a general online linear programming problem whose formulation encompasses many practical dynamic resource allocation problems, including internet advertising display applications, revenue management, various routing, packing, and auction problems. We propose a model, which under mild assumptions, allows us to design near-optimal learning-based online algorithms that do not require the a priori knowledge about the total number of online requests to come, a first of its kind. We then consider two variants of the problem that relax the initial assumptions imposed on the proposed model.
Cite
@article{arxiv.1208.2596,
title = {Near-Optimal Online Algorithms for Dynamic Resource Allocation Problems},
author = {Patrick Jaillet and Xin Lu},
journal= {arXiv preprint arXiv:1208.2596},
year = {2015}
}