Boosting Chaff's performance by incorporating CSP heuristics

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2833, Issue , 2003, Pages 96-107

  Ansótegui, Carlos ^a   Larrubia, Jose ^a   Manyà, Felip ^a  

^a UNIVERSITY OF LLEIDA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING; CONSTRAINT THEORY; MODEL CHECKING;

COMBINATORIAL PROBLEM; ENCODINGS; EXPERIMENTAL EVIDENCE; GRAPH COLORINGS; SAT SOLVERS; STATE OF THE ART; VARIABLE SELECTION;

CONSTRAINT SATISFACTION PROBLEMS;

EID: 35248813309     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-45193-8_7     Document Type: Article

References (33)

1. C. Ansótegui, R. Béjar, A. Cabiscol, C. M. Li, and F. Manyà. Resolution methods for many-valued CNF formulas. In Fifth International Symposium on the Theory and Applications of Satisfiability Testing, SAT-2002, Cincinnati, USA, pages 156-163, 2002.
2. C. Ansótegui, J. Larrubia, C. M. Li, and F. Manyà. Mv-Satz: A SAT solver for many-valued clausal forms. In 4th International Conference Journées de L'Informatique Messine, JIM-2003, Metz, France, 2003.
3. C. Ansótegui, F. Manyà, R. Béjar, and C. Gomes. Solving many-valued SAT encodings with local search. In Proceedings of the Workshop on Probabilistics Approaches in Search, 18th National Conference on Artificial Intelligence, AAAI-2002, Edmonton, Canada, 2002, 2002.
4. R. J. Bayardo and R. C. Schrag. Using CSP look-back techniques to solve real-world SAT instances. In Proceedings of the 14th National Conference on Artificial Intelligence, AAAI'97, Providence/RI, USA, pages 203-208. AAAI Press, 1997.
5. B. Beckert, R. Hähnle, and F. Manyà. Transformations between signed and classical clause logic. In Proceedings, International Symposium on Multiple-Valued Logics, ISMVL'99, Freiburg, Germany, pages 248-255. IEEE Press, Los Alamitos, 1999.
6. B. Beckert, R. Hähnle, and F. Manyà. The SAT problem of signed CNF formulas. In D. Basin, M. D'Agostino, D. Gabbay, S. Matthews, and L. Viganò, editors, Labelled Deduction, volume 17 of Applied Logic Series, pages 61-82. Kluwer, Dordrecht, 2000.
7. R. Béjar, A. Cabiscol, C. Fernández, F. Manyà, and C. P. Gomes. Capturing structure with satisfiability. In 7th International Conference on Principles and Practice of Constraint Programming, CP-2001,Paphos, Cyprus, pages 137-152. Springer LNCS 2239, 2001.
8. R. Béjar, R. Hähnle, and F. Manyà. A modular reduction of regular logic to classical logic. In Proceedings, 31st International Symposium on Multiple-Valued Logics (ISMVL), Warsaw, Poland, pages 221-226. IEEE CS Press, Los Alamitos, 2001.
9. R. Béjar and F. Manyà. A comparison of systematic and local search algorithms for regular CNF formulas. In Proceedings of the 5th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU'99, London, England, pages 22-31. Springer LNAI 1638, 1999.
10. R. Béjar and F. Manyà. Solving the round robin problem using prepositional logic. In Proceedings of the 17th National Conference on Artificial Intelligence, AAAI-2000, Austin/TX, USA, pages 262-266. AAAI Press, 2000.
11. C. Bessière and J. Régin. Refining the basic constraint propagation algorithm. In Proceedings of IJCAI'01, pages 309-315, 2001.
12. J. Culberson. Graph coloring page: The flat graph generator. See http://web.cs.ualberta.ca/~joe/Coloring/Generators/flat.html, 1995.
13. M. Davis, G. Logemann, and D. Loveland. A machine program for theorem-proving. Communications of the ACM, 5:394-397, 1962.
14. M. Davis and H. Putnam. A computing procedure for quantification theory. Journal of the ACM, 7(3):201-215, 1960.
15. R. Génisson and P. Jégou. Davis and Putnam were already checking forward. In Proceedings of the 12th European Conference on Artificial Intelligence (ECAI), Budapest, Hungary, pages 180-184, 1996.
16. I. P. Gent. Arc consistency in SAT. In Proceedings of the 15th European Conference on Artificial Intelligence (ECAI), Lyon, France, pages -, 2002.
17. R. Haralick and G. Elliot. Increasing tree search efficiency for constraint satisfaction problems. Artificial Intelligence, 14:263-313, 1980.
18. H. Hoos. SATLIB: A collection of SAT tools and data. See www.satlib.org, 1999.
19. H. A. Kautz, Y. Ruan, D. Achlioptas, C. P. Gomes, B. Selman, and M. Stickel. Balance and filtering in structured satisfiable problems. In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI'01, Seattle/WA, USA, pages 351-358, 2001.
20. H. A. Kautz and B. Selman. Pushing the envelope: Planning, prepositional logic, and stochastic search. In Proceedings of the 14th National Conference on Artificial Intelligence, AAAI'96, Portland/OR, USA, pages 1194-1201. AAAI Press, 1996.
21. C. M. Li and Anbulagan. Heuristics based on unit propagation for satisfiability problems. In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI'97, Nagoya, Japan, pages 366-371. Morgan Kaufmann, 1997.
22. C. M. Li and Anbulagan. Look-ahead versus look-back for satisfiability problems. In Proceedings of the 3rd International Conference on Principles of Constraint Programming, CP'97, Linz, Austria, pages 341-355. Springer LNCS 1330, 1997.
23. F. Manyà, R. Béjar, and G. Escalada-Imaz. The satisfiability problem in regular CNF-formulas. Soft Computing: A Fusion of Foundations, Methodologies and Applications, 2(3):116-123, 1998.
24. J. P. Marques-Silva and L. Guerra. Algorithms for satisfiability in combinational circuits based on backtrack search and recursive learning. In Proc. of XII Symposium on Integrated Circuits and Systems Design (SBCCI), 1999.
25. M. Moskewicz, C. Madigan, Y. Zhao, L. Zhang, and S. Malik. Chaff: Engineering an efficient sat solver. In 39th Design Automation Conference, 2001.
26. D. Sabin and E. Freuder. Contradicting conventional wisdom in constraint satisfaction. In Proceedings of ECAI'94, pages 125-129, 1994.
27. B. Selman and H. A. Kautz. Domain-independent extensions of GSAT: Solving large structured satisfiability problems. In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI'93, Chambery, France, pages 290-295. Morgan Kaufmann, 1993.
28. B. Selman, H. A. Kautz, and B. Cohen. Noise strategies for improving local search. In Proceedings of the 12th National Conference on Artificial Intelligence, AAAI'94, Seattle/WA, USA, pages 337-343. AAAI Press, 1994.
29. B. Selman, H. Levesque, and D. Mitchell. A new method for solving hard satisfiability problems. In Proceedings of the 10th National Conference on Artificial Intelligence, AAAI'92, San Jose/CA, USA, pages 440-446. AAAI Press, 1992.
30. J. P. M. Silva and K. A. Sakallah. GRASP: A search algorithm for propositional satisfiability. IEEE Transactions on Computers, 48(5):506-521, 1999.
31. B. Smith and M. Dyer. Locating the phase transition in binary constraint satisfaction problems. Artificial Intelligence, 81:155-181, 1996.
32. M. Velev and R. Bryant. Effective use of boolean satisfiability procedures in the formal verification of superscalar and vliw microprocessors. In 38th Design Automation Conference (DAC '01), 2001.
33. T. Walsh. SAT v CSP. In Proceedings of the 6th International Conference on Principles of Constraint Programming, CP-2000, Singapore, pages 441-456. Springer LNCS 1894, 2000.