Restoring CSP Satisfiability with MaxSAT

  • Authors:
  • Inês Lynce;Joao Marques-Silva

  • Affiliations:
  • (Correspd.) INESC-ID/IST, Technical University of Lisbon, Lisbon, Portugal. ines@sat.inesc-id.pt;Complex & Adaptive Systems Laboratory, School of Computer Science and Informatics, University College Dublin, Ireland. jpms@ucd.ie

  • Venue:
  • Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
  • Year:
  • 2011

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Abstract

The extraction of a Minimal Unsatisfiable Core (MUC) in a Constraint Satisfaction Problem (CSP) aims to identify a subset of constraints that make a CSP instance unsatisfiable. Recent work has addressed the identification of a Minimal Set of Unsatisfiable Tuples (MUST) in order to restore the CSP satisfiability with respect to that MUC. A two-step algorithm has been proposed: first, a MUC is identified, and second, a MUST in the MUC is identified. This paper proposes an integrated algorithm for restoring satisfiability in a CSP, making use of a MaxSAT solver. The proposed approach encodes the CSP instance as a partial MaxSAT instance, in such a way that solving the MaxSAT instance corresponds to identifying the smallest set of tuples to be removed from the CSP instance to restore satisfiability. Experimental results illustrate the feasibility of the approach.