Abstract
It is well-known that the order in which variables are processed in a DPLL-style SAT algorithm can have a substantial effect on its run-time. Different heuristics, such as VSIDS [2], have been proposed in the past to obtain good variable orderings. However, most of these orderings are general-purpose and do not take into account the additional structural information that is available on a higher problem description level. Thus, structural, problem-dependent strategies have been proposed (see, e.g., the work of Marques-Silva and Lynce on special strategies for cardinality constraints [1]).
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References
Marques-Silva, J., Lynce, I.: Towards Robust CNF Encodings of Cardinality Constraints. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 483–497. Springer, Heidelberg (2007)
Moskewicz, M.W., Madigan, C.F., Zhao, Y., Zhang, L., Malik, S.: Chaff: Engineering an efficient SAT solver. In: DAC 2001, pp. 530–535 (2001)
Torlak, E., Jackson, D.: Kodkod: A Relational Model Finder. In: Grumberg, O., Huth, M. (eds.) TACAS 2007. LNCS, vol. 4424, pp. 632–647. Springer, Heidelberg (2007)
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Iser, M., Taghdiri, M., Sinz, C. (2012). Optimizing MiniSAT Variable Orderings for the Relational Model Finder Kodkod. In: Cimatti, A., Sebastiani, R. (eds) Theory and Applications of Satisfiability Testing – SAT 2012. SAT 2012. Lecture Notes in Computer Science, vol 7317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31612-8_46
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DOI: https://doi.org/10.1007/978-3-642-31612-8_46
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