We introduce a new approach for focusing constraint reasoning using so-called streamlining constraints. Such constraints partition the solution space to drive the search first towards a small and structured combinatorial subspace. The streamlining constraints capture regularities observed in a subset of the solutions to smaller problem instances. We demonstrate the effectiveness of our approach by solving a number of hard combinatorial design problems. Our experiments show that streamlining scales significantly beyond previous approaches. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Gomes, C., & Sellmann, M. (2004). Streamlined constraint reasoning. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3258, 274–289. https://doi.org/10.1007/978-3-540-30201-8_22
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