The propositional satisfiability problem (SAT) is one of the most studied NP-complete problems in computer science [1]. Some of the best known methods for solving certain types of SAT instances are stochastic local search algorithms [6]. Pure Additive Weighting Scheme (PAWS) is now one of the best dynamic local search algorithms in the additive weighting category [7]. Fang et. al [3] introduce the island confinement method to speed up the local search algorithms. In this paper, we incorporate the island confinement method into PAWS to speed up PAWS. We show through experiments that, the resulted algorithm, PAWSI, betters PAWS in solving the hard graph coloring and AIS problems. abstract environment. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Kilani, Y., Bsoul, M., Alsarhan, A., & Obeidat, I. (2012). Improving PAWS by the island confinement method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7268 LNAI, pp. 662–670). Springer Verlag. https://doi.org/10.1007/978-3-642-29350-4_78
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