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New algorithms for max restricted path consistency

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Abstract

Max Restricted Path Consistency (maxRPC) is a local consistency for binary constraints that enforces a higher order of consistency than arc consistency. Despite the strong pruning that can be achieved, maxRPC is rarely used because existing maxRPC algorithms suffer from overheads and redundancies as they can repeatedly perform many constraint checks without triggering any value deletions. In this paper we propose and evaluate techniques that can boost the performance of maxRPC algorithms by eliminating many of these overheads and redundancies. These include the combined use of two data structures to avoid many redundant constraint checks, and the exploitation of residues to quickly verify the existence of supports. Based on these, we propose a number of closely related maxRPC algorithms. The first one, maxRPC3, has optimal O(end 3) time complexity, displays good performance when used stand-alone, but is expensive to apply during search. The second one, maxRPC3 rm, has O(en 2 d 4) time complexity, but a restricted version with O(end 4) complexity can be very efficient when used during search. The other algorithms are simple modifications of maxRPC3 rm. All algorithms have O(ed) space complexity when used stand-alone. However, maxRPC3 has O(end) space complexity when used during search, while the others retain the O(ed) complexity. Experimental results demonstrate that the resulting methods constantly outperform previous algorithms for maxRPC, often by large margins, and constitute a viable alternative to arc consistency on some problem classes.

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References

  1. Balafoutis, T., Paparrizou, A., Stergiou, K., & Walsh, T. (2010). Improving the performance of maxRPC. In Proceedings of CP-2010 (pp. 69–83).

  2. Balafoutis, T., & Stergiou, K. (2008). Exploiting constraint weights for revision ordering in arc consistency algorithms. In ECAI-08 workshop on modeling and solving problems with constraints.

  3. Bartak, R., & Erben, R. (2004). A new algorithm for singleton arc consistency. In Proceedings of FLAIRS conference-2004.

  4. Berlandier, P. (1995). Improving domain filtering using restricted path consistency. In Proceedings of IEEE CAIA-95 (pp. 32–37).

  5. Bessiere, C. (1994). Arc-consistency and arc-consistency again. Artificial Intelligence, 65, 179–190.

    Article  Google Scholar 

  6. Bessiere, C., Cardon, S., Debruyne, R., & Lecoutre, C. (2011). Efficient algorithms for singleton arc consistency. Constraints, 16, 25–53.

    Article  MathSciNet  MATH  Google Scholar 

  7. Bessiere, C., & Debruyne, R. (2005). Optimal and suboptimal singleton arc consistency algorithms. In Proceedings of IJCAI-2005 (pp. 54–59).

  8. Bessière, C., Freuder, E. C., & Régin, J. C. (1995). Using inference to reduce arc consistency computation. In Proceedings of IJCAI’95 (pp. 592–599).

  9. Bessiere, C., Katsirelos, G., Narodytska, N., Quimper, C. G., & Walsh, T. (2009). Decompositions of all different, global cardinality and related constraints. In Proceedings of IJCAI-2009 (pp. 419–424).

  10. Bessière, C., Régin, J. C., Yap, R., & Zhang, Y. (2005). An optimal coarse-grained arc consistency algorithm. Artificial Intelligence, 165(2), 165–185.

    Article  MathSciNet  MATH  Google Scholar 

  11. Boussemart, F., Hemery, F., & Lecoutre, C. (2004). Revision ordering heuristics for the constraint satisfaction problem. In CP-2004 workshop on constraint propagation and implementation, Toronto, Canada.

  12. Boussemart, F., Hemery, F., Lecoutre, C., & Sais, L. (2004). Boosting systematic search by weighting constraints. In Proceedings of ECAI-2004 (pp. 482–486). Valencia, Spain.

  13. Debruyne, R. (1999). A strong local consistency for constraint satisfaction. In Proceedings of ICTAI-99 (pp. 202–209).

  14. Debruyne, R., & Bessière, C. (1997). From restricted path consistency to max-restricted path consistency. In Proceedings of CP-97 (pp. 312–326).

  15. Debruyne, R., & Bessière, C. (2001). Domain filtering consistencies. Journal of Artificial Intelligence Research, 14, 205–230.

    MathSciNet  MATH  Google Scholar 

  16. Freuder, E., & Elfe, C. (1996). Neighborhood inverse consistency preprocessing. In Proceedings of AAAI’96 (pp. 202–208).

  17. Gent, I. P., MacIntyre, E., Prosser, P., Shaw, P., & Walsh, T. (1997). The constraindedness of arc consistency. In Proceedings of CP-97 (pp. 327–340).

  18. Grandoni, F., & Italiano, G. (2003). Improved algorithms for max-restricted path consistency. In Proceedings of CP’03 (pp. 858–862).

  19. Haralick, R. M., & Elliott, G. L. (1980). Increasing tree search efficiency for constraint satisfaction problems. Artificial Intelligence, 14, 263–314.

    Article  Google Scholar 

  20. Lecoutre, C., & Cardon, S. (2005). A greedy approach to establish singleton arc consistency. In Proceedings of IJCAI-2005 (pp. 199–204).

  21. Lecoutre, C., Cardon, S., & Vion, J. (2007). Conservative dual consistency. In Proceedings of AAAI-07 (pp. 237–242).

  22. Lecoutre, C., & Hemery, F. (2007). A study of residual supports in arc consistency. In Proceedings of IJCAI-2007 (pp. 125–130).

  23. Likitvivatanavong, C., Zhang, Y., Bowen, J., Shannon, S., & Freuder, E. (2007). Arc consistency during search. In Proceedings of IJCAI-2007 (pp. 137–142).

  24. Montanari, U. (1974). Network of constraints: Fundamental properties and applications to picture processing. Information Science, 7, 95–132.

    Article  MathSciNet  Google Scholar 

  25. Quimper, C. G., & Walsh, T. (2006). Global grammar constraints. In Proceedings of CP-2006 (pp. 751–755).

  26. Sabin, D., & Freuder, E. C. (1997). Understanding and improving the MAC algorithm. In Proceedings of CP-1997 (pp. 167–181).

  27. Schulte, C., & Stuckey, P. J. (2008). Efficient constraint propagation engines. ACM Transactions on Programming Languages and Systems, 31(1), 1–43.

    Article  Google Scholar 

  28. Vion, J., & Debruyne, R. (2009). Light algorithms for maintaining max-RPC during search. In Proceedings of SARA-2009.

  29. Wallace, R., & Freuder, E. (1992). Ordering heuristics for arc consistency algorithms. In AI/GI/VI (pp. 163–169). Vancouver, British Columbia, Canada.

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Correspondence to Kostas Stergiou.

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This paper is an extended version of [1] that appeared in the proceedings of CP-2010.

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Balafoutis, T., Paparrizou, A., Stergiou, K. et al. New algorithms for max restricted path consistency. Constraints 16, 372–406 (2011). https://doi.org/10.1007/s10601-011-9110-y

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