Generalised arc consistency for the AllDifferent constraint: An empirical survey

Artificial Intelligence

Volumn 172, Issue 18, 2008, Pages 1973-2000

  Gent, Ian P ^a   Miguel, Ian ^a   Nightingale, Peter ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

Author keywords

AllDifferent; Constraint programming; Constraint satisfaction problems; Global constraints

Indexed keywords

CAVITY RESONATORS; CODES (SYMBOLS); COMPUTER PROGRAMMING; CONSTRAINT THEORY; GRANULAR MATERIALS; QUERY LANGUAGES; SURVEYS;

ALLDIFFERENT; ARC CONSISTENCIES; COMPUTATIONAL COSTS; CONNECTED COMPONENTS; CONSTRAINT MODELS; CONSTRAINT PROGRAMMING; CONSTRAINT SATISFACTION PROBLEMS; GLOBAL CONSTRAINTS; KEY TECHNIQUES; PROPAGATION PROCESSES; SPEED-UP;

CONSTRAINED OPTIMIZATION;

EID: 56249120655     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2008.10.006     Document Type: Article

References (29)

1. Aggoun A., Chan D., Dufresne P., Falvey E., Grant H., Harvey W., Herold A., Macartney G., Meier M., Miller D., Mudambi S., Novello S., Perez B., van Rossum E., Schimpf J., Shen K., Tsahageas P.A., and de Villeneuve D.H. Eclipse user manual release 5.10, 2006. http://eclipse-clp.org/
2. 1.5 sqrt(m / log n)). Information Processing Letters 37 4 (1991) 237-240
3. Berge C. Graphs and Hypergraphs (1973), North-Holland Publishing Company
4. Carlsson M., and Schulte C. Finite domain constraint programming systems, 2002. Available from. ftp://ftp.sics.se/pub/isl/papers/FD%20Systems.pdf
5. Simon Colton, Ian Miguel, Constraint generation via automated theory formation, in: Proceedings of the Seventh International Conference on Principles and Practice of Constraint Programming, 2001, pp. 575-579
6. Cormen T.H., Leiserson C.E., and Rivest R.L. Introduction to Algorithms (1990), MIT Press
7. Costa M.-C. Persistency in maximum cardinality bipartite matchings. Operations Research Letters 15 3 (1994) 143-149
8. Eppstein D. Implementation of Hopcroft-Karp algorithm in Python, 2002. http://www.ics.uci.edu/~eppstein/
9. Ian P. Gent, Chris Jefferson, Ian Miguel, Minion: A fast, scalable, constraint solver, in: Proceedings 17th European Conference on Artificial Intelligence (ECAI 2006), 2006, pp. 98-102
10. Ian P. Gent, Chris Jefferson, Ian Miguel, Watched literals for constraint propagation in minion, in: Proceedings 12th International Conference on the Principles and Practice of Constraint Programming (CP 2006), 2006
11. Ian P. Gent, Christopher Jefferson, Ian Miguel, Peter Nightingale, Data structures for generalised arc consistency for extensional constraints, in: Proceedings of the Twenty Second Conference on Artificial Intelligence (AAAI-07), 2007, pp. 191-197
12. Ian P. Gent, Ian Miguel, Andrea Rendl, Tailoring solver-independent constraint models: A case study with essence' and minion, in: Proceedings of SARA, 2007, pp. 184-199
13. Hnich B., Miguel I., Gent I.P., and Walsh T. CSPLib: A problem library for constraints. http://csplib.org/
14. 2.5 algorithm for maximum matchings in bipartite graphs. SIAM Journal on Computing 2 4 (1973) 225-231
15. ILOG Solver 6.0 User Manual, ILOG S.A., 2003
16. Katriel I. Expected-case analysis for delayed filtering. In: Beck J.C., and Smith B.M. (Eds). CPAIOR. Lecture Notes in Computer Science vol. 3990 (2006), Springer 119-125
17. Henry A. Kautz, Yongshao Ruan, Dimitris Achlioptas, Carla P. Gomes, Bart Selman, Mark E. Stickel, Balance and filtering in structured satisfiable problems, in: Proceedings of IJCAI-2001, 2001, pp. 351-358
18. Knuth D.E., and Raghunathan A. The problem of compatible representatives. SIAM Journal of Discrete Mathematics 5 3 (1992) 422-427
19. Mikael Z. Lagerkvist, Christian Schulte, Advisors for incremental propagation, in: Proceedings 13th Principles and Practice of Constraint Programming (CP 2007), 2007, pp. 409-422
20. Claude-Guy Quimper, Toby Walsh. The all different and global cardinality constraints on set, multiset and tuple variables, in: Recent Advances in Constraints, LNAI, vol. 3419, 2006
21. Jean-Charles Régin, A filtering algorithm for constraints of difference in CSPs, in: Proceedings 12th National Conference on Artificial Intelligence (AAAI 94), 1994, pp. 362-367
22. Schulte C., and Stuckey P.J. Speeding up constraint propagation. In: Wallace M. (Ed). Tenth International Conference on Principles and Practice of Constraint Programming. Toronto, Canada. Lecture Notes in Computer Science vol. 3258 (September, 2004), Springer-Verlag 619-633
23. Schulte C., and Tack G. Views and iterators for generic constraint implementations. Recent Advances in Constraints (2005). Lecture Notes in Artificial Intelligence vol. 3978 (2006), Springer-Verlag 118-132
24. João C. Setubal, New experimental results for bipartite matching, in: Proceedings of netflow93, Technical Report TR-21/93, Dipartamento de Informatica, Università di Pisa, 1993, pp. 211-216
25. João C. Setubal, Sequential and parallel experimental results with bipartite matching algorithms, Technical Report EC-96-09, Institute of Computing, University of Campinas, Brasil, 1996
26. Kostas Stergiou, Toby Walsh, The difference all-difference makes, in: Proceedings IJCAI'99, 1999
27. Tarjan R. Depth-first search and linear graph algorithms. SIAM Journal on Computing 1 2 (1972) 146-160
28. Willem-Jan van Hoeve, The alldifferent constraint: A survey, in: Proceedings Sixth Annual Workshop of the ERCIM Working Group on Constraints, 2001
29. Wallace M. Practical applications of constraint programming. Constraints 1 1/2 (1996) 139-168