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.


Algorithm Selection Test Instance Constraint Programming Training Instance Portfolio Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuri Malitsky
    • 1
  • Meinolf Sellmann
    • 2
  1. 1.Department of Computer ScienceBrown UniversityUSA
  2. 2.IBM Research WatsonUSA

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