Abstract
An attractive mechanism to specify global constraints in rostering and other domains is via formal languages. For instance, the Regular and Grammar constraints specify constraints in terms of the languages accepted by an automaton and a context-free grammar respectively. Taking advantage of the fixed length of the constraint, we give an algorithm to transform a context-free grammar into an automaton. We then study the use of minimization techniques to reduce the size of such automata and speed up propagation. We show that minimizing such automata after they have been unfolded and domains initially reduced can give automata that are more compact than minimizing before unfolding and reducing. Experimental results show that such transformations can improve the size of rostering problems that we can “model and run”.
NICTA is funded by the Australian Government’s Department of Broadband, Communications, and the Digital Economy and the Australian Research Council.
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Katsirelos, G., Narodytska, N., Walsh, T. (2009). Reformulating Global Grammar Constraints. In: van Hoeve, WJ., Hooker, J.N. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2009. Lecture Notes in Computer Science, vol 5547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01929-6_11
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DOI: https://doi.org/10.1007/978-3-642-01929-6_11
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