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International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming

CPAIOR 2012: Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems pp 244–259Cite as

Instance-Specific Algorithm Configuration as a Method for Non-Model-Based Portfolio Generation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7298))

Abstract

Instance-specific algorithm configuration generalizes both instance-oblivious algorithm tuning as well as algorithm portfolio generation. ISAC is a recently proposed non-model-based approach for tuning solver parameters dependent on the specific instance that needs to be solved. While ISAC has been compared with instance-oblivious algorithm tuning systems before, to date a comparison with portfolio generators and other instance-specific algorithm configurators is crucially missing. In this paper, among others, we provide a comparison with SATzilla, as well as three other algorithm configurators: Hydra, DCM and ArgoSmart. Our experimental comparison shows that non-model-based ISAC significantly outperforms prior state-of-the-art algorithm selectors and configurators. The following study was the foundation for the best sequential portfolio at the 2011 SAT Competition.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Brown University, USA

    Yuri Malitsky

  2. IBM Research Watson, USA

    Meinolf Sellmann

Authors
  1. Yuri Malitsky
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  2. Meinolf Sellmann
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Editor information

Editors and Affiliations

  1. École des Mines de Nantes, 4, rue Alfred Kastler, 44307, Nantes Cedex 3, France

    Nicolas Beldiceanu

  2. École des Mines de Nantes, 4 rue Alfred Kastler, 44307, Nantes Cedex 3, France

    Narendra Jussien

  3. Institut de Mathématiques Appliquées, 44 rue Rabelais, 49008, Angers Cedex 01, France

    Éric Pinson

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© 2012 Springer-Verlag Berlin Heidelberg

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Malitsky, Y., Sellmann, M. (2012). Instance-Specific Algorithm Configuration as a Method for Non-Model-Based Portfolio Generation. In: Beldiceanu, N., Jussien, N., Pinson, É. (eds) Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems. CPAIOR 2012. Lecture Notes in Computer Science, vol 7298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29828-8_16

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  • DOI: https://doi.org/10.1007/978-3-642-29828-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29827-1

  • Online ISBN: 978-3-642-29828-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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