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Strong local consistency algorithms for table constraints

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Abstract

Table constraints are important in constraint programming as they are present in many real problems from areas such as configuration and databases. As a result, numerous specialized algorithms that achieve generalized arc consistency (GAC) on table constraints have been proposed. Since these algorithms achieve GAC, they operate on one constraint at a time. In this paper we propose new filtering algorithms for positive table constraints that achieve stronger local consistency properties than GAC by exploiting intersections between constraints. The first algorithm, called maxRPWC+, is a domain filtering algorithm that is based on the local consistency maxRPWC and extends the GAC algorithm of Lecoutre and Szymanek (2006). The second algorithm extends the state-of-the-art STR-based algorithms to stronger relation filtering consistencies, i.e., consistencies that can remove tuples from constraints’ relations. Experimental results from benchmark problems demonstrate that the proposed algorithms are quite competitive with standard GAC algorithms like STR2 in some classes of problems with intersecting table constraints, being orders of magnitude faster in some cases.

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Authors and Affiliations

  1. Montpellier, France

    Anastasia Paparrizou

  2. Thessaloniki, Greece

    Kostas Stergiou

Authors
  1. Anastasia Paparrizou
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  2. Kostas Stergiou
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Correspondence to Anastasia Paparrizou.

Additional information

Some results included in this paper first appeared in [31].

This author (Anastasia Paparrizou) has been funded by the EU project ICON (FP7-284715).

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Paparrizou, A., Stergiou, K. Strong local consistency algorithms for table constraints. Constraints 21, 163–197 (2016). https://doi.org/10.1007/s10601-014-9179-1

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