Skip to main content
Log in

Saving constraint checks in maintaining coarse-grained generalized arc consistency

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Constraint check plays a central role in establishing generalized arc consistency which is widely used to solve constraint satisfaction problems. In this paper, we propose a new generalized arc consistency algorithm, called GTR, which ensures that the tuples that have been checked to be allowed by a constraint will never be checked again. For each constraint, GTR maintains a dynamic list of the tuples that were checked to be allowed by this constraint and check their validities to identify some values with supports. It is equipped with a mechanism avoiding redundant validity checks. The basic GAC3 algorithm is employed to find a support for the rest values and to add new tuples to the dynamic list. The experiments show that maintaining GTR during search saves a number of constraint checks. It also brings some improvements over cpu time while solving some CSPs with tight constraints.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. The two instances are downloaded from http://www.cril.univ-artois.fr/~lecoutre/benchmarks.html.

References

  1. Bessière C (1994) Arc-consistency and arc-consistency again. Artif Intell 65:179–190

    Article  Google Scholar 

  2. Bessière C, Fargier H, Lecoutre C (2013) Global inverse consistency for interactive constraint satisfaction Proceedings of CP’13, pp 159–174

    Google Scholar 

  3. Bessière C, Freuder EC, Régin JC (1999) Using constraint metaknowledge to reduce arc consistency computation. Artif Intell 107:125–148

    Article  MathSciNet  MATH  Google Scholar 

  4. Bessière C, Régin JC (1997) Arc consistency for general constraint networks: preliminary results Proceedings of IJCAI’97, pp 398–404

    Google Scholar 

  5. Bessière C, Régin JC, Yap R, Zhang Y (2005) An optimal coarse-grained arc consistency algorithm. Artif Intell 165:165–185

    Article  MathSciNet  MATH  Google Scholar 

  6. Boussemart F, Hemery F, Lecoutre C, Sais L (2004) Boosting systematic search by weighting constraints Proceedings of ECAI’04, pp 146–150

    Google Scholar 

  7. Gomes C, Selman B, Kautz H (1998) Boosting combinatorial search through randomization Proceedings of AAAI’98, pp 431–437

    Google Scholar 

  8. Lecoutre C (2011) STR2: optimized simple tabular reduction for table constraints. Constraints 16:341–371

    Article  MathSciNet  MATH  Google Scholar 

  9. Lecoutre C, Boussemart F, Hemery F (2003) Exploiting multidirectionality in coarsegrained arc consistency algorithms Proceedings of CP’03, pp 480–494

    Google Scholar 

  10. Lecoutre C, Hemery F (2007) A study of residual supports in arc consistency Proceedings of IJCAI’07, pp 125–130

    Google Scholar 

  11. Lecoutre C, Likitvivatanavong C, Shannon S, Yap R, Zhang Y (2008) Maintaining arc consistency with multiple residues. Constraint Program Lett 2:3–19

    Google Scholar 

  12. Li H (2017) Narrowing support searching range in maintaining arc consistency for solving constraint satisfaction problems. IEEE access. doi:10.1109/ACCESS.2017.2690672

  13. Li H, Liang Y, Guo J, Li Z (2013) Making simple tabular reduction works on negative table constraints Proceedings of AAAI’13, pp 1629–1630

    Google Scholar 

  14. Likitvivatanavong C, Zhang Y, Bowen J, Freuder EC (2004) Arc consistency in MAC a new perspective Proceedings of CPAI’04 workshop held with CP’04, pp 93–107

    Google Scholar 

  15. Likitvivatanavong C, Zhang Y, Shannon C, Bowen J, Freuder EC (2007) Arc consistency during search Proceedings of IJCAI’07, pp 137–142

    Google Scholar 

  16. Mackworth AK (1977) Consistency in networks of relations. Artif Intell 8:99–118

    Article  MATH  Google Scholar 

  17. Mohr R, Henderson TC (1986) Arc and path consistency revisited. Artif Intell 28:225–233

    Article  Google Scholar 

  18. Sabin D, Freuder EC (1994) Contradicting conventional wisdom in constraint satisfaction Proceedings of ECAI’94, pp 125–129

    Google Scholar 

  19. Ullmann JR (2007) Partition search for non-binary constraint satisfaction. Inf Sci 177:3639–3678

    Article  MathSciNet  MATH  Google Scholar 

  20. van Dongen MRC (2004) Saving support-checks does not always save time. Artif Intell Rev 21:317–334

  21. Wang R, Xia W, Yap R, Li Z (2016) Optimizing simple table reduction with bitwise representation Proceedings of IJCAI’16, pp 787–793

    Google Scholar 

  22. Walsh T (1999) Search in a small world Proceedings of IJCAI’99, pp 1172–1177

    Google Scholar 

Download references

Acknowledgments

This work was supported by the Fundamental Research Funds for the Central Universities (NO. 2412016KJ034), the Education Department of Jilin Province (Project NO. JJKH20170911KJ) and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University (NO.93K172017K06).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Minghao Yin.

Ethics declarations

Conflict of interests

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, H., Li, R. & Yin, M. Saving constraint checks in maintaining coarse-grained generalized arc consistency. Neural Comput & Applic 31 (Suppl 1), 499–508 (2019). https://doi.org/10.1007/s00521-017-3015-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-017-3015-7

Keywords

Navigation