Abstract
The Boolean satisfiability problem (SAT) has many applications in electronic design automation (EDA) as well as theoretical computer science. Most SAT solvers for EDA problems use the DPLL algorithm and conflict analysis dependent decision heuristics. When the search starts, the heuristics have little or no information about the structure of the CNF. In this work, an algorithm for initializing dynamic decision heuristics is evolved using genetic programming. The open-source SAT solver MiniSAT v1.12 is used. Using the best algorithm evolved, an advantage was found for solving unsatisfiable EDA SAT problems.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kibria, R.H., Li, Y. (2006). Optimizing the Initialization of Dynamic Decision Heuristics in DPLL SAT Solvers Using Genetic Programming. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds) Genetic Programming. EuroGP 2006. Lecture Notes in Computer Science, vol 3905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11729976_30
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DOI: https://doi.org/10.1007/11729976_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33143-8
Online ISBN: 978-3-540-33144-5
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