Exploiting inference rules to compute lower bounds for MAX-SAT solving?

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2007, Pages 2334-2339

  Lin, Han ^a   Su, Kaile ^a,b  

^a SUN YAT SEN UNIVERSITY   (China)

^b GRIFFITH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EFFICIENT SOLVERS; INFERENCE RULES; LOGICAL FRAMEWORKS; LOWER BOUNDS; MAX-SAT; MAX-SAT PROBLEMS; NEW FUNCTIONS;

FORMAL LOGIC; LINEAR PROGRAMMING;

ARTIFICIAL INTELLIGENCE;

EID: 57749190762     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. T. Alsinet, F. Manyà, and J. Planes. Improved branch and bound algorithms for max-sat. In Proceedings of the 6th International Conference on the Theory and Applications of Satisfiability Testing, 2003.
2. N. Bansal and V. Raman. Upper bounds for maxsat: further improved. In Proceedings of ISAAC 1999, pages 247-258, 1999.
3. B. Borchers and J. Furman. A two-phase exact algorithm for max-sat and weighted max-sat problems. Journal of Combinatorial Optimization, 2(4):299-306, 1999. (Pubitemid 129644219)
4. M. Davis, G. Logemann, and G. Loveland. A machine program for theorem proving. Communications of the ACM, 5:394-397, 1962.
5. S. de Givry, J. Larrosa, P. Meseguer, and T. Schiex. Solving max-sat as weighted csp. In Proc. of the 9th CP, pages 363-376, Kinsale, Ireland, 2003. Springer LNCS 2833.
6. J. Gramm, E.A. Hirsch, R. Niedermeier, and P. Rossmanith. Worst-case upper bounds for max-2-sat with application to max-cut. Discrete Applied Mathematics, 130(2):139-155, 2003.
7. Federico Heras and Javier Larrosa. New inference rules for efficient max-sat solving. In Proceedings of the 21st AAAI, Boston, Massachusetts, July 2006.
8. R.G. Jeroslow and J. Wang. Solving propositional satisfiability problems. Annals of Mathematics and Artificial Intelligence, 1:167-187, 1990.
9. Henry Kautz and Bart Selman. The state of sat. Discrete and Applied Math, 2005.
10. Javier Larrosa and Federico Heras. Resolution in max-sat and its relation to local consistency in weighted csps. In Proceedings of the 19th IJCAI, Edinburgh, Scotland, 2005.
11. Chu Min Li, Felip Manyà, and Jordi Planes. Exploiting unit propagation to compute lower bounds in branch and bound max-sat solvers. In Proceedings of the 11th International Conference on Principles and Practice of Constraint Programming, pages 403-414, Sitges, Spain, 2005. Springer LNCS 3709.
12. Chu-Min Li, Felip Manyà, and Jordi Planes. Detecting disjoint inconsistent subformulas for computing lower bounds for max-sat. In Proceedings of Twenty- First National Conference on Artificial Intelligence (AAAI 2006), July 2006.
13. J. D. Park. Using weighted max-sat engines to solve mpe. In Proceedings of 18th AAAI, pages 682-687, 2002.
14. H. Shen and H. Zhang. Study of lower bound functions for max-2-sat. In Proceedings of AAAI-2004, pages 185-190, 2004.
15. Dawn M. Strickland, Earl Barnes, and Joel S. Sokol. Optimal protein structure alignment using maximum cliques. Operations Research, 53(3):389-402, May-June 2005.
16. M. Vasquez and J. Hao. A logic-constrained knapsack formulation and a tabu algorithm for the daily photograph scheduling of an earth observation satellite. Journal of Computational Optimization and Applications, 20(2), 2001.
17. Z. Xing and W. Zhang. Maxsolver: An efficient exact algorithm for (weighted) maximum satisfiability. Artificial Intelligence, 164(1-2):47-80, 2005. (Pubitemid 40454430)
18. Ke Xu and Wei Li. Many hard examples in exact phase transitions. Theoretical Computer Science, 355:291-302, 2006.
19. H. Xu, R. Rutenbar, and K. Sakallah. sub-sat: a formulation for relaxed boolean satisfiability with applications in routing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 22(6):814-820, June 2003.
20. Ke Xu, Frederic Boussemart, Fred Hemery, and Christophe Lecoutre. A simple model to generate hard satisfiable instances. In Proceedings of 19th International Joint Conference on Artificial Intelligence (IJCAI 2005), pages 337-342, Edinburgh, Scotland, 2005.