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Boosting Local Search Thanks to cdcl

  • Gilles Audemard
  • Jean-Marie Lagniez
  • Bertrand Mazure
  • Lakhdar Saïs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6397)

Abstract

In this paper, a novel hybrid and complete approach for propositional satisfiability, called SatHys (Sat Hybrid Solver), is introduced. It efficiently combines the strength of both local search and cdcl based sat solvers. Considering the consistent partial assignment under construction by the cdcl sat solver, local search is used to extend it to a model of the Boolean formula, while the cdcl component is used by the local search one as a strategy to escape from a local minimum. Additionally, both solvers heavily cooperate thanks to relevant information gathered during search. Experimentations on SAT instances taken from the last competitions demonstrate the efficiency and the robustness of our hybrid solver with respect to the state-of-the-art cdcl based, local search and hybrid SAT solvers.

Keywords

Local Search Random Instance Partial Assignment Stochastic Local Search Partial Interpretation 
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 2010

Authors and Affiliations

  • Gilles Audemard
    • 1
  • Jean-Marie Lagniez
    • 1
  • Bertrand Mazure
    • 1
  • Lakhdar Saïs
    • 1
  1. 1.CRIL - CNRS UMR 8188Université Lille-Nord de FranceArtois

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