Selection of search strategies for solving 3-SAT problems
References
- Aloul, F., Mneimneh, M. and Sakallah, K. (2002). ZBDD-based backtrack search SAT solver, Proceedings of the International Workshop on Logic Synthesis, Lake Tahoe, CA, USA, pp. 131–136.
- Arangú, M. and Salido, M.A. (2011). A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems, International Journal of Applied Mathematics and Computer Science21(4): 733–744, DOI: 10.2478/v10006-011-0058-2.
- Balduccini, M., Gelfond, M. and Nogueira, M. (2006). Answer set based design of knowledge systems, Annals of Mathematics and Artificial Intelligence47(1–2): 183–219.
- Brewka, G. (1991). Cumulative default logic: In defense of nonmonotonic inference rules, Artificial Intelligence50(2): 183–205.
- Davis, M., Logemann, G. and Loveland, D. (1962). A machine program for theorem proving, Communications of the ACM5(7): 394–397.
- Davis, M. and Putnam, H. (1960). A computing procedure for quantification theory, Journal of the ACM7(3): 201–215.
- DIMACS (1993). CNF benchmarks database, ftp://dimacs.rutgers.edu/pub/challenge /sat/benchmarks/cnf/.
- Gelfond, M. and Lifschitz, V. (1988). The stable model semantics for logic programming, in R.A. Kowalski and K.A. Bowen (Eds.), Proceedings of the International Logic Programming Conference and Symposium, MIT Press, Cambridge, MA, pp. 1070–1080.
- Han, H., Somenzi, F. and Jin, H. (2010). Making deduction more effective in SAT solvers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems29(8): 1271–1284.
- Hu, Y., Shih, V., Majumdar, R. and He, L. (2008). Exploiting symmetries to speed up SAT-based Boolean matching for logic synthesis of FPGAs, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems27(10): 1751–1760.
- Lukasiewicz, T. and Straccia, U. (2008). Tightly coupled fuzzy description logic programs under the answer set semantics for the semantic web, International Journal on Semantic Web and Information Systems4(3): 68–89.
- Marques-Silva, J. and Sakallah, K. (1999). GRASP: A search algorithm for propositional satisfiability, IEEE Transactions on Computers48(5): 506–521.
- Moskewicz, M., Madigan, C., Zhao, Y., Zhang, L. and Malik, S. (2001). Chaff: Engineering an efficient SAT solver, Proceedings of the Design Automation Conference, Las Vegas, NV, USA, pp. 530–535.
- Opara, A. and Kania, D. (2010). Decomposition-based logic synthesis for PAL-based CPLDs, International Journal of Applied Mathematics and Computer Science20(2): 367–384, DOI: 10.2478/v10006-010-0027-1.
- Pułka, A. (2009). Decision supporting system based on fuzzy default reasoning, Proceedings of the IEEE Human Systems Interaction Conference, HSI’09, Catania, Italy, pp. 32–39.
- Pułka, A. (2011). An effective SAT-solving mechanism with backtrack controlled by FDL, Proceedings of the 18th International Conference on Mixed Design of Integrated Circuits and Systems (MIXDES), Gliwice, Poland, pp. 252–257.
- Reiter, R. (1980). A logic for default reasoning, Artificial Intelligence13(1): 81–132.
- Suyama, T., Yokoo, M. and Nagoya, A. (1999). Solving satisfiability problems on FPGAs using experimental unit propagation heuristic, parallel and distributed processing, in J. Rolim (Ed.), Parallel and Distributed Processing, Lecture Notes in Computer Science, Vol. 1586, Springer-Verlag, Berlin, pp. 709–711.
- Tille, D., Eggersgluss, S. and Drechsler, R. (2010). Incremental solving techniques for SAT-based ATPG, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems29(7): 1125–1130.
- Wyrwoł, B. and Hrynkiewicz, E. (2013). Decomposition of the fuzzy inference system for implementation in the FPGA structure, International Journal of Applied Mathematics and Computer Science23(2): 473–483, DOI: 10.2478/amcs-2013-0036.
- Yin, L., He, F., Hung, W., Song, X. and Gu, M. (2012). Maxterm covering for satisfiability, IEEE Transactions on Computers61(3): 420–426.
- Zadeh, L.A. (2006). Generalized theory of uncertainty (GTU)—principal concepts and ideas, Computational Statistics and Data Analysis51(1): 15–46.
- Zadeh, L.A. (2008). Is there a need for fuzzy logic?, Information Sciences: An International Journal178(13): 2751–2779.
Language: English
Page range: 283 - 297
Submitted on: Jan 13, 2013
Published on: Jun 26, 2014
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
Keywords:
Related subjects:
© 2014 Andrzej Pułka, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.