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On getting rid of the preprocessing minimization step in MUC-finding algorithms

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Abstract

When a constraint network is unsatisfiable, it can be of prime importance to provide the network designer with a full-fledged explanation of what causes the absence of any solution to the network. In this respect, minimal unsatisfiable cores (in short, MUCs) form the basis for such an explanation. Efficient MUC extractors are often made of an initial incomplete minimization step that delivers an upper-approximation of a MUC, followed by a refinement step. The first step is believed crucial for the global performance of the whole approach. In this paper, its actual importance is investigated. Especially, it is shown that the first step can be skipped when the refinement process dynamically exploits the information from its own search.

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Authors and Affiliations

  1. CRIL, CNRS umr 8188, Université d’Artois rue Jean Souvraz SP18, 62307, Lens, France

    Éric Grégoire, Jean-Marie Lagniez & Bertrand Mazure

Authors
  1. Éric Grégoire
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  2. Jean-Marie Lagniez
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  3. Bertrand Mazure
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Correspondence to Bertrand Mazure.

Additional information

This paper is a revised and expanded version of a contribution presented at IEEE ICTAI’13. It has been supported in part by the Région Nord/Pas-de-Calais, by the EC through a FEDER grant and in part by the ANR TUPLES project No10-BLAN-0210.

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Grégoire, É., Lagniez, JM. & Mazure, B. On getting rid of the preprocessing minimization step in MUC-finding algorithms. Constraints 20, 414–432 (2015). https://doi.org/10.1007/s10601-015-9187-9

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