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Dynamic Global Constraints in Backtracking Based Environments

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Abstract

Global constraints provide strong filtering algorithms to reduce the search space when solving large combinatorial problems. In this paper we propose to make the global constraints dynamic, i.e., to allow extending the set of constrained variables during search. We describe a generic dynamisation technique for an arbitrary monotonic global constraint and we compare it with the semantic-based dynamisation for the alldifferent constraint. At the end we sketch a dynamisation technique for non-monotonic global constraints. A comparison with existing methods to model dynamic problems is given as well.

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  1. Faculty of Mathematics and Physics, Charles University, Malostranské náměstí 2/25, 118 00, Praha, Czech Republic

    Roman Barták

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  1. Roman Barták
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Barták, R. Dynamic Global Constraints in Backtracking Based Environments. Annals of Operations Research 118, 101–119 (2003). https://doi.org/10.1023/A:1021805623454

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