Abstract
We introduce a notion of equally constrained variables of a constraint network. We propose a method of pruning that uses the notion. We combine the proposed method of pruning with FC-CBJ and call the resulting algorithm FC-CBJ-EQ. Our experimental results show that FC-CBJ-EQ outperforms FC-CBJ on constraint networks that encode randomly generated instances of graph k-coloring and of the subgraph isomorphism problems.
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Razgon, I., Meisels, A. (2005). Pruning by Equally Constrained Variables. In: Faltings, B.V., Petcu, A., Fages, F., Rossi, F. (eds) Recent Advances in Constraints. CSCLP 2004. Lecture Notes in Computer Science(), vol 3419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11402763_3
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DOI: https://doi.org/10.1007/11402763_3
Publisher Name: Springer, Berlin, Heidelberg
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