Dynamic Global Constraints in Backtracking Based Environments

Roman Barták ()

Annals of Operations Research, 2003, vol. 118, issue 1, 119 pages

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. Copyright Kluwer Academic Publishers 2003

Keywords: global constraints; filtering algorithm; dynamic models (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1023/A:1021805623454

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