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A Probabilistic 3—SAT Algorithm Further Improved

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2285))

Abstract

In [Sch99], Schöning proposed a simple yet efficient randomized algorithm for solving the k-SAT problem. In the case of 3-SAT, the algorithm has an expected running time of poly(n)·E(4/3)n = O(1.3334n) when given a formula F on n variables. This was the up to now best running time known for an algorithm solving 3-SAT. Here, we describe an algorithm which improves upon this time bound by combining an improved version of the above randomized algorithm with other randomized algorithms. Our new expected time bound for 3-SAT is O(1.3302n).

Supported in part by DFG grant Sch 302/5-2.

Supported in part by JSPS/NSF cooperative research: Complexity Theory for Strategic Goals, 1998–2001.

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References

  1. B. Aspvall, M.F. Plass, R.E. Tarjan, A linear-time algorithm for testing the truth of certain quantified Boolean formulas, Information Processing Letters, 8(3), 121–123, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  2. E. Dantsin, A. Goerdt, E.A. Hirsch, and U. Schöning, Deterministic algorithms for k-SAT based on covering codes and local search, in Proc. 27th International Colloquium on Automata, Languages and Programming, ICALP’00, Lecture Notes in Comp. Sci. 1853, 236–247, 2000.

    Google Scholar 

  3. E.A. Hirsch, New worst-case upper bounds for SAT, Journal of Automated Reasoning, 24(4), 397–420, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  4. O. Kullmann, New methods for 3-SAT decision and worst-case analysis, Theoretical Computer Science, 223(1/2), 1–72, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  5. B. Monien and E. Speckenmeyer, Solving satisfiability in less than 2n steps, Discrete Applied Mathematics, 10, 287–295, 1985.

    Article  MATH  MathSciNet  Google Scholar 

  6. R. Paturi, P. Pudlák, M.E. Saks, and F. Zane, An improved exponentialtime algorithm for k-SAT, in Proc. of the 39th Ann. IEEE Sympos. on Foundations of Comp. Sci. (FOCS’98), IEEE, 628–637, 1998.

    Google Scholar 

  7. U. Schöning, A probabilistic algorithm for k-SAT and constraint satisfaction problems, in Proc. of the 40th Ann. IEEE Sympos. on Foundations of Comp. Sci. (FOCS’99), IEEE, 410–414, 1999.

    Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Hofmeister, T., Schöning, U., Schuler, R., Watanabe, O. (2002). A Probabilistic 3—SAT Algorithm Further Improved. In: Alt, H., Ferreira, A. (eds) STACS 2002. STACS 2002. Lecture Notes in Computer Science, vol 2285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45841-7_15

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  • DOI: https://doi.org/10.1007/3-540-45841-7_15

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43283-8

  • Online ISBN: 978-3-540-45841-8

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