LMHS: A SAT-IP Hybrid MaxSAT Solver

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9710)

Abstract

We describe LMHS, an open-source weighted partial maximum satisfiability (MaxSAT) solver. LMHS is a hybrid SAT-IP MaxSAT solver that implements the implicit hitting set approach to MaxSAT. On top of the main algorithm, LMHS offers integrated preprocessing, solution enumeration, an incremental API, and the use of a choice of SAT and IP solvers. We describe the main features of LMHS, and give empirical results on the influence of preprocessing and the choice of the underlying SAT and IP solvers on the performance of LMHS.

References

  1. 1.
    Achterberg, T.: SCIP: solving constraint integer programs. Math. Program. Comput. 1(1), 1–41 (2009)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Argelich, J., Li, C.M., Manyá, F., Planes, J.: Max-SAT 2015: Tenth Max-SAT Evaluation (2015). http://www.maxsat.udl.cat/15/
  3. 3.
    Belov, A., Järvisalo, M., Marques-Silva, J.: Formula preprocessing in MUS extraction. In: Piterman, N., Smolka, S.A. (eds.) TACAS 2013 (ETAPS 2013). LNCS, vol. 7795, pp. 108–123. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  4. 4.
    Belov, A., Morgado, A., Marques-Silva, J.: SAT-based preprocessing for MaxSAT. In: McMillan, K., Middeldorp, A., Voronkov, A. (eds.) LPAR-19 2013. LNCS, vol. 8312, pp. 96–111. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  5. 5.
    Berg, J., Saikko, P., Järvisalo, M.: Improving the effectiveness of SAT-based preprocessing for MaxSAT. In: Proceedings of IJCAI, pp. 239–245. AAAI Press (2015)Google Scholar
  6. 6.
    Berg, J., Saikko, P., Järvisalo, M.: Re-using auxiliary variables for MaxSAT preprocessing. In: Proceedings of ICTAI, pp. 813–820. IEEE (2015)Google Scholar
  7. 7.
    Biere, A.: Yet another local search solver and Lingeling and friends entering the SAT competition 2014. In: Proceedings of SAT Competition 2014, vol. B-2014-2, pp. 39–40. Department of Computer Science Series of Publications B, University of Helsinki (2014)Google Scholar
  8. 8.
    Davies, J., Bacchus, F.: Solving MAXSAT by solving a sequence of simpler SAT instances. In: Lee, J. (ed.) CP 2011. LNCS, vol. 6876, pp. 225–239. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Davies, J., Bacchus, F.: Exploiting the power of MIP solvers in MaxSAT. In: Järvisalo, M., Van Gelder, A. (eds.) SAT 2013. LNCS, vol. 7962, pp. 166–181. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Davies, J., Bacchus, F.: Postponing optimization to speed up MAXSAT solving. In: Schulte, C. (ed.) CP 2013. LNCS, vol. 8124, pp. 247–262. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Eén, N., Biere, A.: Effective preprocessing in SAT through variable and clause elimination. In: Bacchus, F., Walsh, T. (eds.) SAT 2005. LNCS, vol. 3569, pp. 61–75. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  12. 12.
    Eén, N., Sörensson, N.: An extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Heras, F., Morgado, A., Marques-Silva, J.: MaxSAT-based encodings for group MaxSAT. AI Commun. 28(2), 195–214 (2015)MathSciNetGoogle Scholar
  14. 14.
  15. 15.
    Järvisalo, M., Heule, M.J.H., Biere, A.: Inprocessing rules. In: Gramlich, B., Miller, D., Sattler, U. (eds.) IJCAR 2012. LNCS, vol. 7364, pp. 355–370. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  16. 16.
    Karp, R.M.: Implicit hitting set problems and multi-genome alignment. In: Amir, A., Parida, L. (eds.) CPM 2010. LNCS, vol. 6129, pp. 151–151. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Manthey, N.: Coprocessor 2.0 – a flexible CNF simplifier. In: Cimatti, A., Sebastiani, R. (eds.) SAT 2012. LNCS, vol. 7317, pp. 436–441. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  18. 18.
    Moreno-Centeno, E., Karp, R.M.: The implicit hitting set approach to solve combinatorial optimization problems with an application to multigenome alignment. Oper. Res. 61(2), 453–468 (2013)MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Saikko, P., Malone, B., Järvisalo, M.: MaxSAT-based cutting planes for learning graphical models. In: Michel, L. (ed.) CPAIOR 2015. LNCS, vol. 9075, pp. 347–356. Springer, Heidelberg (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Helsinki Institute for Information Technology HIIT, Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland

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