Solving Constraint Satisfaction Problems with SAT Technology
A Boolean Satisfiability Testing Problem (SAT) is a combinatorial problem to find a Boolean variable assignment which satisfies all given Boolean formulas. Recent performance improvement of SAT technologies makes SAT-based approaches applicable for solving hard and practical combinatorial problems, such as planning, scheduling, hardware/software verification, and constraint satisfaction.
Sugar is a SAT-based constraint solver based on a new encoding method called order encoding which was first used to encode job-shop scheduling problems by Crawford and Baker. In the order encoding, a comparison x ≤ a is encoded by a different Boolean variable for each integer variable x and integer value a. The Sugar solver shows a good performance for a wide variety of problems, and became the winner of the GLOBAL categories in 2008 and 2009 CSP solver competitions.
The talk will provide an introduction to modern SAT solvers, SAT encodings, implementation techniques of the Sugar solver, and its performance evaluation.
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- 2.de Kleer, J.: A comparison of ATMS and CSP techniques. In: Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI 1989), pp. 290–296 (1989)Google Scholar
- 5.Gent, I.P.: Arc consistency in SAT. In: Proceedings of the 15th European Conference on Artificial Intelligence (ECAI 2002), pp. 121–125 (2002)Google Scholar
- 6.Iwama, K., Miyazaki, S.: SAT-variable complexity of hard combinatorial problems. In: Proceedings of the IFIP 13th World Computer Congress, pp. 253–258 (1994)Google Scholar
- 10.Crawford, J.M., Baker, A.B.: Experimental results on the application of satisfiability algorithms to scheduling problems. In: Proceedings of the 12th National Conference on Artificial Intelligence (AAAI 1994), pp. 1092–1097 (1994)Google Scholar
- 12.Nabeshima, H., Soh, T., Inoue, K., Iwanuma, K.: Lemma reusing for SAT based planning and scheduling. In: Proceedings of the International Conference on Automated Planning and Scheduling 2006 (ICAPS 2006), pp. 103–112 (2006)Google Scholar
- 13.Soh, T., Inoue, K., Tamura, N., Banbara, M., Nabeshima, H.: A SAT-based method for solving the two-dimensional strip packing problem. Journal of Algorithms in Cognition, Informatics and Logic (2009) (to appear)Google Scholar
- 14.Tamura, N., Banbara, M.: Sugar: a CSP to SAT translator based on order encoding. In: Proceedings of the 2nd International CSP Solver Competition, pp. 65–69 (2008)Google Scholar
- 15.Tamura, N., Tanjo, T., Banbara, M.: System description of a SAT-based CSP solver Sugar. In: Proceedings of the 3rd International CSP Solver Competition, pp. 71–75 (2008)Google Scholar
- 16.Tanjo, T., Tamura, N., Banbara, M.: Sugar++: a SAT-based Max-CSP/COP solver. In: Proceedings of the 3rd International CSP Solver Competition, pp. 77–82 (2008)Google Scholar
- 17.Eén, N., Sörensson, N.: An extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)Google Scholar