Abstract
We present a preprocessing procedure for the Subgraph Isomorphism problem, and report empirical results of applying it to Generating Satisfiable SAT instances using the Random Subgraph Isomorphism model. The experimental results show that the preprocessor makes the easy-hard-easy pattern of empirical hardness clear for all SAT solvers tested. Moreover, the use of the procedure does not significantly influence the location or the empirical hardness of the instances at the hardness peak, thus preserving the model’s main characteristics.
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References
Anton, C., Olson, L.: Generating satisfiable SAT instances using random subgraph isomorphism. In: Proceeding of Canadian Conference on AI 2009, pp. 16–26 (2009)
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Anton, C., Neal, C. (2010). Notes on Generating Satisfiable SAT Instances Using Random Subgraph Isomorphism. In: Farzindar, A., Kešelj, V. (eds) Advances in Artificial Intelligence. Canadian AI 2010. Lecture Notes in Computer Science(), vol 6085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13059-5_36
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DOI: https://doi.org/10.1007/978-3-642-13059-5_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13058-8
Online ISBN: 978-3-642-13059-5
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