Evaluating ASP and commercial solvers on the CSPLib

Constraints

Volumn 13, Issue 4, 2008, Pages 407-436

  Mancini, Toni ^a   Micaletto, Davide ^a   Patrizi, Fabio ^a   Cadoli, Marco ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Answer set programming; Constraint programming; Declarative constraint modelling; Experimental evaluation among solvers; OPL; Problem reformulation

Indexed keywords

CHLORINE COMPOUNDS; CONSTRAINT THEORY; TECHNOLOGY;

ANSWER SET PROGRAMMING; ARITHMETIC CONSTRAINTS; COMBINATORIAL PROBLEMS; COMMERCIAL SOLVERS; CONSTRAINT PROGRAMMING; DECLARATIVE CONSTRAINT MODELLING; EXPERIMENTAL EVALUATION AMONG SOLVERS; EXPERIMENTAL METHODOLOGY; GLOBAL CONSTRAINTS; INSTANCE SELECTION; MARGINAL EFFECTS; MODELLING TECHNIQUES; OPL; PROBLEM REFORMULATION; REFORMULATION TECHNIQUES; RELATIVE PERFORMANCE; SMODELS; STRUCTURAL SYMMETRY; SYMMETRY-BREAKING;

RESEARCH;

EID: 52249113653     PISSN: 13837133     EISSN: 15729354     Source Type: Journal    
DOI: 10.1007/s10601-007-9028-6     Document Type: Article

References (38)

1. Bosch, R., & Trick, M. (2002). Constraint programming and hybrid formulations for three life designs. In Proceedings of the fourth international workshop on integration of AI and OR techniques in constraint programming for combinatorial optimization problems (CPAIOR 2002) (pp. 77-91). Le Croisic.
2. M. Cadoli T. Mancini 2006 Automated reformulation of specifications by safe delay of constraints Artificial Intelligence 170 8-9 779 801
3. Cadoli, M., & Mancini, T. (2007). Using a theorem prover for reasoning on constraint problems. Applied Artificial Intelligence, 21(4/5), 383-404.
4. Cadoli, M., Mancini, T., Micaletto, D., & Patrizi, F. (2006). Evaluating ASP and commercial solvers on the CSPLib. In Proceedings of the seventeenth european conference on artificial intelligence (ECAI 2006) (pp. 68-72). IOS Press.
5. Cadoli, M., Mancini, T., & Patrizi, F. (2006). SAT as an effective solving technology for constraint problems. In Proceedings of the sixteenth international symposium on methodologies for intelligent systems (ISMIS 2006). Lecture Notes in Computer Science (Vol. 4203, pp. 540-549). Bari, Italy: Springer.
6. M. Cadoli A. Schaerf 2005 Compiling problem specifications into SAT Artificial Intelligence 162 89 120
7. Castillo, E., Conejo, A. J., Pedregal, P., Garca, R., & Alguacil, N. (2001). Building and solving mathematical programming models in engineering and science. John Wiley & Sons.
8. B. M. W. Cheng K. M. F. Choi J. H.-M. Lee J. C. K. Wu 1999 Increasing constraint propagation by redundant modeling: An experience report Constraints 4 2 167 192
9. Crawford, J. M., Ginsberg, M. L., Luks, E. M., & Roy, A. (1996). Symmetry-breaking predicates for search problems. In Proceedings of the fifth international conference on the principles of knowledge representation and reasoning (KR'96) (pp. 148-159). Morgan Kaufmann.
10. A. K. Dewdney 1987 The game life aquires some successors in three dimensions Science American 224 2 112 118
11. Dovier, A., Formisano, A., & Pontelli, E. (2005). A comparison of CLP(FD) and ASP solutions to NP-complete problems. In Proceedings of the twentyfirst international conference on logic programming (ICLP 2005). Lecture Notes in Computer Science (Vol. 3668, pp. 67-82). Springer.
12. Ellman, T. (1993). Abstraction via approximate symmetry. In Proceedings of the thirteenth international joint conference on artificial intelligence (IJCAI'93) (pp. 916-921). Morgan Kaufmann.
13. A. J. Fernández P. M. Hill 2000 A comparative study of eight constraint programming languages over the Boolean and Finite Domains Constraints 5 3 275 301
14. R. A. Finkel V. W. Marek M. Truszczynski 2004 Constraint Lingo: Towards high-level constraint programming Software-Practice and Experience 34 15 1481 1504
15. Flener, P., Frisch, A., Hnich, B., Kiziltan, Z., Miguel, I., Pearson, J., et al. (2002). Breaking row and column symmetries in matrix models. In Proceedings of the eighth international conference on principles and practice of constraint programming (CP 2002). Lecture Notes in Computer Science (Vol. 2470, p. 462). Springer.
16. Fourer, R., Gay, D. M., & Kernigham, B. W. (1993). AMPL: A modeling language for mathematical programming. International Thomson Publishing.
17. Freuder, E. C., & Sabin, D. (1997). Interchangeability supports abstraction and reformulation for multi-dimensional constraint satisfaction. In Proceedings of the fourteenth national conference on artificial intelligence (AAAI'97) (pp. 191-196). AAAI Press/The MIT Press.
18. F. Giunchiglia T. Walsh 1992 A theory of abstraction Artificial Intelligence 57 323 389
19. Gu, J., Purdom, P., Franco, J., & Wah, B. (1997). Algorithms for the satisfiability (SAT) problem: A survey. In Satisfiability Problem: Theory and Applications, DIMACS Series in Discrete Mathematics and Theoretical Computer Science (pp. 19-152). American Mathematical Society.
20. N. Leone G. Pfeifer W. Faber T. Eiter G. Gottlob S. Perri 2006 The DLV system for knowledge representation and reasoning ACM Transactions on Computational Logic 7 3 499 562
21. Lierler, Y., & Maratea, M. (2004). Cmodels-2: SAT-based Answer Set Solver enhanced to non-tight programs. In V. Lifschitz & I. Niemelä (Eds.), Proceedings of the seventh international conference on logic for programming and nonmonotonic reasoning (LPNMR 2004). Lecture Notes in Computer Science (Vol. 2923, pp. 346-350). Fort Lauderdale, FL, USA: Springer.
22. F. Lin Z. Yuting 2004 ASSAT: Computing answer sets of a logic program by SAT solvers Artificial Intelligence 157 1-2 115 137
23. Mancini, T., & Cadoli, M. (2005). Detecting and breaking symmetries by reasoning on problem specifications. In Proceedings of the sixth international symposium on abstraction, reformulation and approximation (SARA 2005). Lecture Notes in Artificial Intelligence (Vol. 3607, pp. 165-181). Springer.
24. T. Mancini M. Cadoli 2007 Exploiting functional dependencies in declarative problem specifications Artificial Intelligence 171 985 1010
25. A. Neumaier O. Shcherbina W. Huyer T. Vinkó 2005 A comparison of complete global optimization solvers Mathematical Programming 103 2 335 356
26. I. Niemelä 1999 Logic programs with stable model semantics as a constraint programming paradigm Annals of Mathematics and Artificial Intelligence 25 3,4 241 273
27. Pelov, N., De Mot, E., & Denecker, M. (2000). Logic Programming approaches for representing and solving Constraint Satisfaction Problems: A comparison. In M. Parigot & A. Voronkov (Eds.), Proceedings of the seventh international conference on logic for programming and automated reasoning (LPAR 2000). Lecture Notes in Computer Science (Vol. 1955, pp. 225-239). Springer.
28. Puget, J.-F. (1993). On the satisfiability of symmetrical constrained satisfaction problems. In H. J. Komorowski & Z. W. Ras (Eds.), Proceedings of the seventh international symposium on methodologies for intelligent systems (ISMIS'93). Lecture Notes in Computer Science (Vol. 689, pp. 350-361). Springer.
29. Ramani, A., Aloul, F. A., Markov, I. L., & Sakallak, K. A. (2004). Breaking instance-independent symmetries in exact graph coloring. In Proceedings of design automation and test conference in europe (DATE 2004) (pp. 324-331). IEEE Computer Society Press.
30. Régin, J.-C. (2003). Global constraints and filtering algorithms. In M. Milano (Ed.) Constraint and Integer Programming - Toward a Unified Methodology, Operations Research/Computer Science Interfaces, Vol. 27, chapter 4. Kluwer Academic Publisher.
31. Shcherbina, O., Neumaier, A., Sam-Haroud, D., Vu, X.-H., & Nguyen, T.-V. (2003). Benchmarking global optimization and constraint satisfaction codes. In Proceedings of the first international workshop on global constraint optimization and constraint satisfaction (COCOS 2002). Lecture Notes in Computer Science (Vol. 2861, pp. 211-222). Springer.
32. Smith, B. M. (2002). A dual graph translation of a problem in 'life'. In Proceedings of the eighth international conference on principles and practice of constraint programming (CP 2002). Lecture Notes in Computer Science (Vol. 2470, pp. 402-414). Springer.
33. Smith, B. M., Stergiou, K., & Walsh, T. (2000). Using auxiliary variables and implied constraints to model non-binary problems. In Proceedings of the seventeenth national conference on artificial intelligence (AAAI 2000) (pp. 182-187). AAAI Press/The MIT Press.
34. Smolka, G. (1995). The Oz programming model. In Computer Science Today: Recent Trends and Developments. Lecture Notes in Computer Science (Vol. 1000, pp. 324-343). Springer.
35. Ullman, J. D. (1988). Principles of database and knowledge base systems, Vol. 1. Computer Science Press.
36. Van Hentenryck, P. (1999). The OPL optimization programming language. The MIT Press.
37. M. Wallace J. Schimpf K. Shen W. Harvey 2004 On benchmarking constraint logic programming platforms. Response to Fernández and Hill's "A comparative study of eight constraint programming languages over the Boolean and Finite Domains" Constraints 9 1 5 34
38. Walsh, T. (2001). Permutation problems and channelling constraints. In R. Nieuwenhuis & A, Voronkov (Eds.), Proceedings of the eighth international conference on logic for programming and automated reasoning (LPAR 2001). Lecture Notes in Computer Science (Vol. 2250, pp. 377-391). Springer.