skip to main content
10.1145/1141277.1141367acmconferencesArticle/Chapter ViewAbstractPublication PagessacConference Proceedingsconference-collections
Article

A new local consistency for weighted CSP dedicated to long domains

Published:23 April 2006Publication History

ABSTRACT

The weighted constraint satisfaction problem (WCSP) is a soft constraint framework with a wide range of applications. Most current complete solvers can be described as a depth-first branch and bound search that maintains some form of local consistency during the search. However, the known consistencies are unable to solve problems with huge domains because of their time and space complexities. In this paper, we adapt the 2B-consistency, a weaker form of arc consistency well-known in classic CSPs, into the bound arc consistency and we provide several algorithms to enforce it.

References

  1. S. Bistarelli, P. Codognet, Y. Georget, and F. Rossi. Labeling and partial local consistency for soft constraint programming. In Proc. PADL 2000, pages 230--248, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Cooper and T. Schiex. Arc consistency for soft constraints. Artificial Intelligence, 154:199--227, 2004.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. D. Gautheret, F. Major, and R. Cedergren. Pattern searching/alignment with RNA primary and secondary structures: an effective descriptor for tRNA. Comp. Appl. Biosc., 6:325--331, 1990.]]Google ScholarGoogle Scholar
  4. J. Gorodkin, L. L. Heyer, and G. D. Stormo. Finding the most significant common sequence and structure motifs in a set of RNA sequences. Nucleic Acids Research, 25:3724--3732, 1997.]]Google ScholarGoogle ScholarCross RefCross Ref
  5. P. V. Hentenryck, Y. Deville, and C.-M. Teng. A generic arc-consistency algorithm and its specializations. Artificial Intelligence, 57(2-3):291--321, 1992.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Khatib, P. Morris, R. Morris, and F. Rossi. Temporal constraint reasoning with preferences. In Proc. IJCAI 2001, pages 322--327, 2001.]]Google ScholarGoogle Scholar
  7. J. Larrosa. Node and arc consistency in weighted CSP. In Proc. AAAI'02, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Larrosa, P. Meseguer, and T. Schiex. Maintaining reversible DAC for Max-CSP. Artificial Intelligence, 17(1):149--163, 1999.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. Larrosa and T. Schiex. Solving Weighted CSP by Maintaining Arc-consistency. Artificial Intelligence, 159(1-2):1--26, 2004.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. O. Lhomme. Consistency techniques for numeric CSPs. In Proc. IJCAI 1993, pages 232--238, 1993.]]Google ScholarGoogle Scholar
  11. T. Petit, J.-C. Régin, and C. Bessière. Meta-constraints on violations for over constrained problems. In Proc. ICTAI'00, pages 358--365, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. T. Petit, J.-C. Régin, and C. Bessière. Range-based algorithm for Max-CSP. In Proc. CP'02, pages 280--294, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. T. Schiex. Arc consistency for soft constraints. In Proc. CP'00, pages 411--424, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. T. Schiex, H. Fargier, and G. Verfaillie. Valued constraint satisfaction problems: Hard and easy problems. In Proc. IJCAI 1995, 1995.]]Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A new local consistency for weighted CSP dedicated to long domains

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SAC '06: Proceedings of the 2006 ACM symposium on Applied computing
          April 2006
          1967 pages
          ISBN:1595931082
          DOI:10.1145/1141277

          Copyright © 2006 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 23 April 2006

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • Article

          Acceptance Rates

          Overall Acceptance Rate1,650of6,669submissions,25%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader