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arXiv · 1206.3286

New Techniques for Algorithm Portfolio Design

Matthew Streeter·Stephen F. Smith
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Abstract

We present and evaluate new techniques for designing algorithm portfolios. In our view, the problem has both a scheduling aspect and a machine learning aspect. Prior work has largely addressed one of the two aspects in isolation. Building on recent work on the scheduling aspect of the problem, we present a technique that addresses both aspects simultaneously and has attractive theoretical guarantees. Experimentally, we show that this technique can be used to improve the performance of state-of-the-art algorithms for Boolean satisfiability, zero-one integer programming, and A.I. planning.

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Matthew Streeter, Stephen F. Smith. 2012-06-13. New Techniques for Algorithm Portfolio Design. https://arxiv.org/abs/1206.3286

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