A totally unimodular description of the consistent value polytope for binary constraint programming

Authors:
Ionuţ D. Aron;Daniel H. Leventhal;Meinolf Sellmann
Affiliations:
Department of Computer Science, Brown University, Providence, RI;Department of Computer Science, Brown University, Providence, RI;Department of Computer Science, Brown University, Providence, RI
Venue:
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2006

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Abstract

We present a theoretical study on the idea of using mathematical programming relaxations for filtering binary constraint satisfaction problems. We introduce the consistent value polytope and give a linear programming description that is provably tighter than a recently studied formulation. We then provide an experimental study that shows that, despite the theoretical progress, in practice filtering based on mathematical programming relaxations continues to perform worse than standard arc-consistency algorithms for binary constraint satisfaction problems.