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Domain k-Wise Consistency Made as Simple as Generalized Arc Consistency

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2014)

Abstract

In Constraint Programming (CP), Generalized Arc Consistency (GAC) is the central property used for making inferences when solving Constraint Satisfaction Problems (CSPs). Developing simple and practical filtering algorithms based on consistencies stronger than GAC is a challenge for the CP community. In this paper, we propose to combine k-Wise Consistency (kWC) with GAC, where kWC states that every tuple in a constraint can be extended to every set of k − 1 additional constraints. Our contribution is as follows. First, we derive a domain-filtering consistency, called Domain k-Wise Consistency (DkWC), from the combination of kWC and GAC. Roughly speaking, this property corresponds to the pruning of values of GAC, when enforced on a CSP previously made kWC. Second, we propose a procedure to enforce DkWC, relying on an encoding of kWC to generate a modified CSP called k-interleaved CSP. Formally, we prove that enforcing GAC on the k-interleaved CSP corresponds to enforcing DkWC on the initial CSP. Consequently, we show that the strong DkWC can be enforced very easily in constraint solvers since the k-interleaved CSP is rather immediate to generate and only existing GAC propagators are required: in a nutshell, DkWC is made as simple and practical as GAC. Our experimental results show the benefits of our approach on a variety of benchmarks.

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Mairy, JB., Deville, Y., Lecoutre, C. (2014). Domain k-Wise Consistency Made as Simple as Generalized Arc Consistency. In: Simonis, H. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2014. Lecture Notes in Computer Science, vol 8451. Springer, Cham. https://doi.org/10.1007/978-3-319-07046-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-07046-9_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07045-2

  • Online ISBN: 978-3-319-07046-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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