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Solving SAT problem by heuristic polarity decision-making algorithm 被引量:3

Solving SAT problem by heuristic polarity decision-making algorithm
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摘要 This paper presents a heuristic polarity decision-making algorithm for solving Boolean satisfiability (SAT). The algorithm inherits many features of the current state-of-the-art SAT solvers, such as fast BCP, clause recording, restarts, etc. In addition, a preconditioning step that calculates the polarities of variables according to the cover distribution of Karnaugh map is introduced into DPLL procedure, which greatly reduces the number of conflicts in the search process. The proposed approach is implemented as a SAT solver named DiffSat. Experiments show that DiffSat can solve many "real-life" instances in a reasonable time while the best existing SAT solvers, such as Zchaff and MiniSat, cannot. In particular, DiffSat can solve every instance of Bart benchmark suite in less than 0.03 s while Zchaff and MiniSat fail under a 900 s time limit. Furthermore, DiffSat even outperforms the outstanding incomplete algorithm DLM in some instances. This paper presents a heuristic polarity decision-making algorithm for solving Boolean satisfiability (SAT). The algorithm inherits many features of the current state-of-the-art SAT solvers, such as fast BCP, clause recording, restarts, etc. In addition, a preconditioning step that calculates the polarities of variables according to the cover distribution of Karnaugh map is introduced into DPLL procedure, which greatly reduces the number of conflicts in the search process. The proposed approach is implemented as a SAT solver named DiffSat. Experiments show that DiffSat can solve many "real-life" instances in a reasonable time while the best existing SAT solvers, such as Zchaff and MiniSat, cannot. In particular, DiffSat can solve every instance of Bart benchmark suite in less than 0.03 s while Zchaff and MiniSat fail under a 900 s time limit. Furthermore, DiffSat even outperforms the outstanding incomplete algorithm DLM in some instances.
出处 《Science in China(Series F)》 2007年第6期915-925,共11页 中国科学(F辑英文版)
基金 the National Natural Science Foundation of China (Grant Nos. 90207002, 90307017, 60773125 and 60676018) National Science Foundation (Grant Nos. CCR-0306298) China Postdoctoral Science Foundation (Grant No. KLH1202005) the Natural Science Foundation of Shanghai City (Grant No. 06ZR14016)
关键词 SAT problem DPLL complete algorithm DECISION-MAKING SAT problem, DPLL, complete algorithm, decision-making
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  • 1[1]Burch, J. R., .Singhal, V., Tight integration of combinational verification methods, in Proceedings of IEEE/ACM International Conference on Computer-Aided Design, New York: The Association for Computing Machinery Inc., 1998, 570-576.
  • 2[2]Biere, A., Cimatti, A., Clarke, E. M. et al., Symbolic model checking using SAT procedure instead of BDDs, In Proceedings of Design Automation Conference, New York: The Association for Computing Machinery Inc., 1999, 317-320.
  • 3[3]Selman, B., Levesque, H., Mitchell, D., A new method for solving hard satisfiability problems, In Proceedings of the 10th National Conference on Artificial (AAAI), Intelligence American Association for Artificial Intelligence Press, 1992, 440-446.
  • 4[4]Selman, B., Kautz, H. A., Cohen, B., Noise strategies for improving local search, In Proceedings of the 12th National Conference on Artificial Intelligence (AAAI), American Association for Artificial Intelligence Press, 1994, 337-343.
  • 5[5]Zhang, L., Madigan, C., Moskewicz, M. et al., Efficient conflict driven learning in a Boolean satisfiability solver, In Proceedings of the 2001 International Conference on Computer-Aided Design, New York: The Association for Computing Machinery Inc., 2001, 279-285.
  • 6[6]Marques-Silva, J., Sakallah, K., GRASP: A search algorithm for propositional satisfiability, IEEE Transactions on Computers, Los Alamitos: IEEE Computer Society, 1999, 48: 506-521.
  • 7[7]Bacchus, F., Enhancing Davis Putnam with extended binary clause reasoning, In Proceedings of 18th National Conference on Artificial Intelligence (AAAI), American Association for Artificial Intelligence Press, 2002, 613-619.
  • 8[8]Li, C. M., Anbulagan, Heuristics based on unit propagation for satisfiability problems, In Proceedings of the International Joint Conference on Artifical Intelligence (IJCAI), San Fransisco: Morgan Kaufmann Publisher, 1997, 366-371.
  • 9[9]Hooker, J. N., Vinay, V., Branch rules for satisfiability, Journal of Automated Reasoning, 1995, 15(3): 359-383.
  • 10[10]Moskewicz, M., Madigan, C., Zhao, Y. et al., Chaff: Engineering an efficient SAT solver, In Proceedings of 38th Conference on Design Automation, New York: The Association for Computing Machinery Inc., 2001, 530-535.

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  • 1罗春,杨军,凌明.基于遗传算法和覆盖率驱动的功能验证向量自动生成算法[J].应用科学学报,2005,23(4):375-379. 被引量:15
  • 2[1]Davis M,Putnam H.A computing procedure for quantification theory[J].Journal of ACM,1960,7(3):201-214.
  • 3[2]Subbarayan S,Pradhan D.NiVER:Non increasing variable elimination resolution for preprocessing SAT instances[C]∥International Conference on Theory and Applications of Satisfiability Testing (SAT2004).Canada:Springer,2004:276-291.
  • 4[3]Davis M,Logemann G,Loveland D.A machine program for theorem-proving[J].Communications of the ACM,1962,5(7):394-397.
  • 5[4]Marques-Silva J P,Sakallah K A.GRASP:A search algorithm for propositional satisfiability[J].IEEE Transactions on Computers,1999,48(5):506-521.
  • 6[5]Moskewicz M W,Madigan C F,Zhao Y,et al.Chaff:engineering an efficient SAT solver[C]∥Proceedings of the 38th Design Automation Conference (DAC).Las Vegas,NV,USA:ACM Press,2001:530-535.
  • 7[6]Goldberg E,Novikov Y.BerkMin:A fast and robust SAT-solver[C]∥Proceedings of Design Automation and Test in Europe (DATE).Le Palais des Congres,Paris,France:IEEE Computer Society,2002:142-149.
  • 8[7]E閚 N,Srensson N.An extensible SAT-solver[J].Theory and Applications of Satisfiability Testing,2004,2919:502-518.
  • 9[8]Jin H S,Somenzi F.Strong conflict analysis for propositional satisfiability[C]∥Proceedings of Design,Automation and Test in Europe (DATE).Munich,Germany:European Design and Automation Association,2006:818-823.
  • 10[11]Shang Y,Wah B W.A discrete lagrangian-based global-search method for solving satisfiability problems[J].Journal of Global Optimization,1998,12(1):61-99.

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