Exploiting short supports for improved encoding of arbitrary constraints into SAT
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Encoding to SAT and applying a highly efficient modern SAT solver is an increasingly popular method of solving finite-domain constraint problems. In this paper we study encodings of arbitrary constraints where unit propagation on the encoding provides strong reasoning. Specifically, unit propagation on the encoding simulates generalised arc consistency on the original constraint. To create compact and efficient encodings we use the concept of short support. Short support has been successfully applied to create efficient propagation algorithms for arbitrary constraints. A short support of a constraint is similar to a satisfying tuple however a short support is not required to assign every variable in scope. Some variables are left free to take any value. In some cases a short support representation is smaller than the table of satisfying tuples by an exponential factor. We present two encodings based on short supports and evaluate them on a set of benchmark problems, demonstrating a substantial improvement over the state of the art.
Akgün , Ö , Gent , I P , Jefferson , C A , Miguel , I J & Nightingale , P W 2016 , Exploiting short supports for improved encoding of arbitrary constraints into SAT . in M Rueher (ed.) , Principles and Practice of Constraint Programming : 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings . Lecture Notes in Computer Science , vol. 9892 , Springer , pp. 3-12 , 22nd International Conference on Principles and Practice of Constraint Programming (CP 2016) , Toulouse , France , 5/09/16 . https://doi.org/10.1007/978-3-319-44953-1_1conference
Principles and Practice of Constraint Programming
© 2016, Springer. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at link.springer.com / https://dx.doi.org/10.1007/978-3-319-44953-1_1
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