Abstract
We define a new heuristic that guides the application of cycle resolution (CR) in MaxSAT, and show that it produces better lower bounds than those obtained by applying CR exhaustively as in Max-DPLL, and by applying CR in a limited way when unit propagation detects a contradiction as in MaxSatz.
This research was funded by MEC research projects TIN2006-15662-C02-02, TIN2007-68005-C04-04, and CONSOLIDER CSD2007-0022, INGENIO 2010.
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References
Li, C.M., Manyà, F., Planes, J.: Exploiting unit propagation to compute lower bounds in branch and bound Max-SAT solvers. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 403–414. Springer, Heidelberg (2005)
Li, C.M., Manyà, F., Planes, J.: Detecting disjoint inconsistent subformulas for computing lower bounds for Max-SAT. In: Proceedings AAAI 2006, pp. 86–91 (2006)
Larrosa, J., Heras, F., de Givry, S.: A logical approach to efficient Max-SAT solving. Artificial Intelligence 172(2–3), 204–233 (2008)
Li, C.M., Manyà, F., Planes, J.: New inference rules for Max-SAT. Journal of Artificial Intelligence Research 30, 321–359 (2007)
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© 2008 Springer-Verlag Berlin Heidelberg
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Li, C.M., Manyà, F., Mohamedou, N.O., Planes, J. (2008). Transforming Inconsistent Subformulas in MaxSAT Lower Bound Computation. In: Stuckey, P.J. (eds) Principles and Practice of Constraint Programming. CP 2008. Lecture Notes in Computer Science, vol 5202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85958-1_46
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DOI: https://doi.org/10.1007/978-3-540-85958-1_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85957-4
Online ISBN: 978-3-540-85958-1
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