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Symmetry Breaking for Maximum Satisfiability

  • Conference paper
Logic for Programming, Artificial Intelligence, and Reasoning (LPAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5330))

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Abstract

Symmetries are intrinsic to many combinatorial problems including Boolean Satisfiability (SAT) and Constraint Programming (CP). In SAT, the identification of symmetry breaking predicates (SBPs) is a well-known, often effective, technique for solving hard problems. The identification of SBPs in SAT has been the subject of significant improvements in recent years, resulting in more compact SBPs and more effective algorithms. The identification of SBPs has also been applied to pseudo-Boolean (PB) constraints, showing that symmetry breaking can also be an effective technique for PB constraints. This paper extends further the application of SBPs, and shows that SBPs can be identified and used inMaximum Satisfiability (MaxSAT), as well as in its most well-known variants, including partial MaxSAT, weighted MaxSAT and weighted partial MaxSAT. As with SAT and PB, symmetry breaking predicates for MaxSAT and variants are shown to be effective for a representative number of problem domains, allowing solving problem instances that current state of the art MaxSAT solvers could not otherwise solve.

This paper extends a preliminary technical report [19] on the same subject.

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Authors and Affiliations

  1. School of Electronics and Computer Science, University of Southampton, UK

    Joao Marques-Silva

  2. IST/INESC-ID, Technical University of Lisbon, Portugal

    Inês Lynce & Vasco Manquinho

Authors
  1. Joao Marques-Silva
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  2. Inês Lynce
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  3. Vasco Manquinho
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Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Doha, Qatar

    Iliano Cervesato

  2. Technische Universität Darmstadt, Germany

    Helmut Veith

  3. University of Manchester, UK

    Andrei Voronkov

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© 2008 Springer-Verlag Berlin Heidelberg

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Marques-Silva, J., Lynce, I., Manquinho, V. (2008). Symmetry Breaking for Maximum Satisfiability. In: Cervesato, I., Veith, H., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2008. Lecture Notes in Computer Science(), vol 5330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89439-1_1

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  • DOI: https://doi.org/10.1007/978-3-540-89439-1_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89438-4

  • Online ISBN: 978-3-540-89439-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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