GASAT: A genetic local search algorithm for the satisfiability problem

Evolutionary Computation

Volumn 14, Issue 2, 2006, Pages 223-253

  Lardeux, Frédéric ^a   Saubion, Frédéric ^a   Hao, Jin Kao ^a  

^a UNIVERSITÉ D'ANGERS   (France)

Author keywords

Evolutionary algorithms; Recombination operators; SAT; Tabu search

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOLOGY; COMPUTER LANGUAGE; COMPUTER PROGRAM; COMPUTER SIMULATION; HUMAN; METHODOLOGY; MOLECULAR EVOLUTION; STATISTICAL MODEL; THEORETICAL MODEL;

ALGORITHMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; EVOLUTION, MOLECULAR; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; PROGRAMMING LANGUAGES; SOFTWARE;

EID: 33747046367     PISSN: 10636560     EISSN: 15309304     Source Type: Journal    
DOI: 10.1162/evco.2006.14.2.223     Document Type: Article

References (40)

1. Benhamou, B. and Sais, L. (1992). Theoretical study of symmetries in prepositional calculus and applications. In CADE'92, pages 281-294.
2. Beresin, M., Levine, E., and Winn, J. (1989). A chessboard coloring problem. The College Mathematics Journal, 20(2):106-114.
3. Biere, A., Cimatti, A., Clarke, E. M., Fujita, M., and Zhu, Y. (1999). Symbolic model checking using SAT procedures instead of BDDs. In Proc. of the Design Automation Conference (DAC'99), pages 317-320.
4. Corne, D., Dorigo, M., Glover, F., Dasgupta, D., Moscato, P., Poli, R., and Price, K. V., editors (1999). New Ideas in Optimization (Part 4: Memetic Algorithms). McGraw-Hill.
5. Davis, M., Logemann, G., and Loveland, D. (1962). A machine program for theorem-proving. Communications of the ACM, 5(7):394-397.
6. De Jong, K. A. and Spears, W. M. (1989). Using genetic algorithm to solve NP-complete problems. In Proc. of the 3rd International Conference on Genetic Algorithms (ICGA'89), pages 124-132, Virginia,USA.
7. Dubois, O., André, P., Boufkhad, Y., and Carlier, J. (1996). SAT versus UNSAT. In Second DIMACS Implementation Challenge: Cliques, Coloring and Satisfiability, volume 26 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 415-436.
8. Dubois, O. and Dequen, G. (2001). A backbone-search heuristic for efficient solving of hard 3-SAT formulae. In Nebel, B., editor, Proc. of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pages 248-253, San Francisco, CA.
9. Eiben, A. E. and van der Hauw, J. K. (1997). Solving 3-SAT by GAs adapting constraint weights. In Proc. of The IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, pages 81-86.
10. Fleurent, C. and Ferland, J. A. (1996). Object-oriented implementation of heuristic search methods for graph coloring, maximum clique, and satisfiability. In Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, volume 26 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 619-652.
11. Galinier, P. and Hao, J.-K. (1999). Hybrid evolutionary algorithms for graph coloring. Journal of Combinatorial Optimization, 3(4):379-397.
12. Garey, M. R. and Johnson, D. S. (1979). Computers and Intractability, A Guide to the Theory of NP-Completeness. W.H. Freeman & Company, San Francisco.
13. Glover, F. and Laguna, M. (1997). Tabu Search. Kluwer Academic Publishers.
14. Gottlieb, J., Marchiori, E., and Rossi, C. (2002). Evolutionary algorithms for the satisfiability problem. Evolutionary Computation, 10(1):35-50.
15. Gottlieb, J. and Voss, N. (2000). Adaptive fitness functions for the satisfiability problem. In Hans-Paul Schwefel, M., editor, Parallel Problem Solving from Nature - PPSN VI 6th International Conference, Paris, France. Springer Verlag. LNCS 1917.
16. Gu, J. and Puri, R. (1995). Asynchronous circuit synthesis with boolean satisfiability. IEEE Transactions on Computer-Aided Design, 14(8):961-973.
17. Hansen, P. and Jaumard, B. (1990). Algorithms for the maximum satisfiability problem. Computing, 44(4):279-303.
18. Hao, J.-K. and Dorne, R. (1994). A new population-based method for satisfiability problems. In Proc. of the 11th European Conf. on Artificial Intelligence, pages 135-139, Amsterdam.
19. Hao, J.-K., Lardeux, R, and Saubion, F. (2003). Evolutionary computing for the satisfiability problem. In Applications of Evolutionary Computing, volume 2611 of LNCS, pages 258-267, University of Essex, England, UK.
20. Hart, W. E., Krasnogor, N., and Smith, J. E., editors (2004). Recent Advances in Memetic Algorithms and Related Search Technologies. Springer-Verlag.
21. Hirsch, E. A. and Kojevnikov, A. (2001). UnitWalk: A new SAT solver that uses local search guided by unit clause elimination. PDMI preprint 9/2001, Steklov Institute of Mathematics at St. Petersburg.
22. Jaumard, B., Stan, M., and Desrosiers, J. (1996). Tabu search and a quadratic relaxation for the satisfiability problem. In Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, volume 26 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 457-478.
23. Kautz, H. A. and Selman, B. (2001). Workshop on theory and applications of satisfiability testing (SAT2001). In Electronic Notes in Discrete Mathematics, volume 9.
24. Li, C. M. (2000). Integrating equivalency reasoning into davis-putnam procedure. In Proc. of the AAAI'00, pages 291-296.
25. Li, C. M. and Anbulagan, A. (1997). Heuristics based on unit propagation for satisfiability problems. In Proc. of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI'97), pages 366-371.
26. Li, C. M., Jurkowiak, B., and Purdom, P. W. (2002). Integrating symmetry breaking into a dll procedure. In Fifth International Symposium on the Theory and Applications of Satisfiability Testing (SAT2002), pages 149-155.
27. Marchiori, E. and Rossi, C. (1999). A flipping genetic algorithm for hard 3-SAT problems. In Proc. of the Genetic and Evolutionary Computation Conference, volume 1, pages 393-400.
28. Mazure, B., Sais, L., and Gregoire, E. (1997). Tabu search for SAT. In Proc. of the AAAI-97/IAAI-97, pages 281-285, Providence, Rhode Island.
29. Merz, P. and Freisleben, B. (1997). Genetic local search for the TSP: New results. In IEEE-CEP: Proc. of The IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, pages 159-164.
30. Mitchell, D. G., Selman, B., and Levesque, H. J. (1992). Hard and easy distributions for SAT problems. In Proc. of AAAI'92, pages 459-465.
31. Monasson, R., Zecchina, R., Kirkpatrick, S., Selman, B., and Troyansky, L. (1999). Determining computational complexity from characteristic 'phase transitions'. Nature, 400(8):133-137.
32. Rossi, C., Marchiori, E., and Kok, J. N. (2000). An adaptive evolutionary algorithm for the satisfiability problem. In Proc. of the ACM Symposium on Applied Computing (SAC '00), pages 463-470. ACM press.
33. Selman, B., Kautz, H. A., and Cohen, B. (1994). Noise strategies for improving local search. In Proc. of the AAAI'94, Vol. 1, pages 337-343.
34. Selman, B., Levesque, H. J., and Mitchell, D. G. (1992). A new method for solving hard satisfiability problems. In Proc. of the AAAI'92, pages 440-446, San Jose, CA.
35. Simon, L., Berre, D. L., and Hirsch, E. A. (2002). The SAT2002 competition. Technical report, Fifth International Symposium on the Theory and Applications of Satisfiability Testing.
36. Spears, W. M. (1996). Simulated annealing for hard satisfiability problems. In Second DIMACS Implementation Challenge: Cliques, Coloring and Satisfiability, volume 26 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 533-558.
37. Syswerda, G. (1989). Uniform crossover in genetic algorithms. In Proc. of the 3rd International Conference on Genetic Algorithms (ICGA'89), pages 2-9, Virginia, USA.
38. Van Gelder, A. (1993). Problem generator mkcnf.c. DIMACS, Challenge archive.
39. Zhang, H. (1997). SATO: An efficient propositional prover. In Proc. of the 14th International Conference on Automated Deduction, volume 1249 of LNAI, pages 272-275, Berlin.
40. Zhang, H. (2002). Generating college conference basketball schedules by a SAT solver. In Proc. of 5th International Symposium on the Theory and Applications of Satisfiability Testing, pages 281-291.