Abstract
The Partial MAX-SAT Problem (PMSAT) is a variant of the MAX-SAT problem that consists of two CNF formulas defined over the same variable set. Its solution must satisfy all clauses of the first formula and as many clauses in the second formula as possible. This study is concerned with the PMSAT solution in setting a two-phase stochastic local search method that takes advantage of an estimated backbone variables of the problem. First experiments conducted on PMSAT instances derived from SAT instances indicate that this new method offers significant performance benefits over state-of-the-art PMSAT techniques.
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References
Beck, J.C., Fox, M.S.: A genetic framework for constraint-directed search and scheduling. AI Magazine 19(4), 101–130 (1998)
Cha, B., Iwama, K., Kambayashi, Y., Miyasaki, S.: Local search for Partial MAX-SAT. In: Proceedings of the 14th of AAAI 1997, pp. 263–265 (1997)
Dubois, O., Dequen, G.: A backbone-search heuristic for efficient solving of hard 3-SAT formulae. In: Proceedings of the 17th IJCAI, pp. 248–253 (2001)
Freuder, E., Wallace, R.: Partial constraint satisfaction. Artificial Intelligence 58(1), 21–70 (1992)
Menaï, M.B.: Solution reuse in Partial MAX-SAT Problem. In: Proceedings of IEEE IRI 2004, pp. 481–486 (2004)
Monasson, R., Zecchina, R., Kirkpatrick, S., Selman, B., Troyansky, L.: Determining computational complexity from characteristic ‘Phase Transition’. Nature 400, 133–137 (1999)
Selman, B., Kautz, H.A., Cohen, B.: Noise strategies for improving local search. In: Proceedings of the 12th AAAI 1994, pp. 337–343 (1994)
Slaney, J., Walsh, T.: Backbones in optimization and approximation. In: Proceedings of the 17th IJCAI, pp. 254–259 (2001)
Telelis, O., Stamatopoulos, P.: Heuristic backbone sampling for maximum satisfiability. In: Proceedings of the 2nd Hellenic Conference on AI, pp. 129–139 (2002)
Zhang, W., Rangan, A., Looks, M.: Backbone guided local search for maximum satisfiability. In: Proceedings of the 18th IJCAI, pp. 1179–1186 (2003)
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El Bachir Menaï, M. (2005). A Two-Phase Backbone-Based Search Heuristic for Partial MAX-SAT – An Initial Investigation. In: Ali, M., Esposito, F. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2005. Lecture Notes in Computer Science(), vol 3533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11504894_94
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DOI: https://doi.org/10.1007/11504894_94
Publisher Name: Springer, Berlin, Heidelberg
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