Abstract
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.
This work was supported in part by the Intelligent Information Systems Institute, Cornell University (AFOSR grant F49620-01-1-0076).
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Gomes, C., Sellmann, M. (2004). Streamlined Constraint Reasoning. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_22
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DOI: https://doi.org/10.1007/978-3-540-30201-8_22
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