Improving Parallel Local Search for SAT

@inproceedings{Arbelaez2011ImprovingPL,
  title={Improving Parallel Local Search for SAT},
  author={Alejandro Arbelaez and Youssef Hamadi},
  booktitle={Learning and Intelligent Optimization},
  year={2011}
}
In this work, our objective is to study the impact of knowledge sharing on the performance of portfolio-based parallel local search algorithms. Our work is motivated by the demonstrated importance of clause-sharing in the performance of complete parallel SAT solvers. Unlike complete solvers, state-of-the-art local search algorithms for SAT are not able to generate redundant clauses during their execution. In our settings, each member of the portfolio shares its best configuration (i.e., one… 

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    2012 IEEE 24th International Conference on Tools with Artificial Intelligence
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