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Clause Sharing in Parallel MaxSAT

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Learning and Intelligent Optimization (LION 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7219))

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Abstract

In parallel MaxSAT solving, sharing learned clauses is expected to help to further prune the search space and boost the performance of a parallel solver. However, not all learned clauses should be shared since it could lead to an exponential blow up in memory and to sharing many irrelevant clauses. The main question is which learned clauses should be shared among the different threads. This paper reviews the existing heuristics for sharing learned clauses, namely, static and dynamic heuristics. Moreover, a new heuristic for clause sharing is presented based on freezing shared clauses. Shared clauses are only incorporated into the solver when they are expected to be useful in the near future. Experimental results show the importance of clause sharing and that the freezing heuristic outperforms other clause sharing heuristics.

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Martins, R., Manquinho, V., Lynce, I. (2012). Clause Sharing in Parallel MaxSAT. In: Hamadi, Y., Schoenauer, M. (eds) Learning and Intelligent Optimization. LION 2012. Lecture Notes in Computer Science, vol 7219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_44

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  • DOI: https://doi.org/10.1007/978-3-642-34413-8_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34412-1

  • Online ISBN: 978-3-642-34413-8

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