Computer Science – Artificial Intelligence
Scientific paper
2010-07-05
Computer Science
Artificial Intelligence
To appear in the Proceedings of the 16th International Conference on Principles and Practice of Constraint Programming 2010 (C
Scientific paper
We study decompositions of the global NVALUE constraint. Our main contribution is theoretical: we show that there are propagators for global constraints like NVALUE which decomposition can simulate with the same time complexity but with a much greater space complexity. This suggests that the benefit of a global propagator may often not be in saving time but in saving space. Our other theoretical contribution is to show for the first time that range consistency can be enforced on NVALUE with the same worst-case time complexity as bound consistency. Finally, the decompositions we study are readily encoded as linear inequalities. We are therefore able to use them in integer linear programs.
Bessiere Christian
Katsirelos George
Narodytska Nina
Quimper Claude-Guy
Walsh Toby
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