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Parallel Local Search for Satisfiability

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Combinatorial Search: From Algorithms to Systems

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Abstract

This chapter studies 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. At each restart point, instead of classically generating a random configuration to start with, each algorithm aggregates the shared knowledge to carefully craft a new starting point. We present several aggregation strategies and evaluate them on a large set of problems.

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Notes

  1. 1.

    http://www.satcompetition.org/2009/.

  2. 2.

    In the following, we use the term configuration as a synonym for assignment for the variables.

  3. 3.

    We performed the same experiment on several instances and observed similar behavior.

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  1. Microsoft Research Cambridge, Cambridge, UK

    Youssef Hamadi

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  1. Youssef Hamadi
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Hamadi, Y. (2013). Parallel Local Search for Satisfiability. In: Combinatorial Search: From Algorithms to Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41482-4_4

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  • DOI: https://doi.org/10.1007/978-3-642-41482-4_4

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  • Print ISBN: 978-3-642-41481-7

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