Large-scale ranking and selection using cloud computing

Authors:
Jun Luo;L. Jeff Hong
Affiliations:
The Hong Kong University of Science and Technology, Hong Kong, China;The Hong Kong University of Science and Technology, Hong Kong, China
Venue:
Proceedings of the Winter Simulation Conference
Year:
2011

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Abstract

Ranking-and-selection (R&S) procedures are often used to select the best configuration from a set of alternatives, and the set typically has fewer than 500 alternatives. However, there are many R&S or simulation optimization problems having thousands to tens of thousands alternatives. In this paper we discuss how to solve these problems using cloud computing. In particular, we discuss how cloud computing changes the paradigm that is currently used to design R&S procedures, and show a specific procedure that works efficiently under cloud computing. We demonstrate the practical usefulness of our procedure on a simulation optimization problem with more than 2000 feasible solutions using a small-scale cloud of CPUs created by us.