International Conference on Principles and Practice of Constraint Programming
Solving Boolean Satisfiability Using Local Search Guided by Unit Clause Elimination
Conference paper First Online: 19 November 2001 DOI:
2239 of the book series
Lecture Notes in Computer Science (LNCS) Cite this paper as: Hirsch E.A., Kojevnikov A. (2001) Solving Boolean Satisfiability Using Local Search Guided by Unit Clause Elimination. In: Walsh T. (eds) Principles and Practice of Constraint Programming — CP 2001. CP 2001. Lecture Notes in Computer Science, vol 2239. Springer, Berlin, Heidelberg Abstract
In this paper we present a new randomized algorithm for SAT combining unit clause elimination and local search. The algorithm is inspired by two randomized algorithms having the best current worst- case upper bounds ([
]and [ 9 ],[ 11 ]). Despite its simplicity, our algorithm performs well on many common benchmarks (we present results of its empirical evaluation). It is also probabilistically approximately complete. 12 Keywords: Boolean satisfiability local search empirical evaluation
Supported by INTAS YSF 99-4044,RFBR 99-01-00113 and RAS Young Scientists Project #1 of the 6th competition (1999).
E. Dantsin, E.A. Hirsch, S. Ivanov,and M. Vsemirnov. Algorithms for SAT and upper bounds on their complexity.ECCC Technical Report 01-012,
J. Gu, P.W. Purdom, J. Franco, and B.W. Wah. Algorithms for satisfiability (SAT)problem:A survey.DIMACS Ser.in DM and TCS 35,1997,pages 19–152.
H.H. Hoos.On the run-time behaviour of stochastic local search algorithms for SAT. In
Stochastic Local Search-Method,Models,Applications.PhD thesis, Department of Computer Science, Darmstadt University of Technology,1998.
H.H. Hoos and T. Stützle. SATLIB.
H.H. Hoos and T. Stützle. Local search algorithms for SAT:An empirical evaluation.
Journal of Automated Reasoning
MATH CrossRef Google Scholar
D.S. Johnson and M.A. Tricks,editors.
Cliques,Coloring and Satisfiability, volume 26 of DIMACS Ser.in DM and TCS.AMS,1996.
D. McAllester, B. Selman,and H. Kautz. Evidence in invariants for local search. In
R. Paturi, P. Pudl ák, M.E. Saks,and F. Zane. An improved exponential-time algorithm for k-SAT. In
S.D. Prestwich. Local search and backtracking vs non-systematic backtracking. In
AAAI 2001 Fall Symposium on Using Uncertainty within Computation.To appear.
U. Schöning. A probabilistic algorithm for k-SAT and constraint satisfaction problems. In
R. Schuler, U. Schöning,and O. Watanabe. An improved randomized algorithm for 3-SAT. Technical Report TR-C146, Dept.of Math.and Comp.Sci.,Tokyo Inst.of Tech.,2001.
D. Schuurmans and F. Southey. Local search characteristics of incomplete SAT procedures. In
Proc.of AAAI’2000,pages 297–302.
B. Selman, H. A. Kautz, and B. Cohen. Noise strategies for improving local search. In
B. Selman, H. Levesque, and D. Mitchell. A new method for solving hard satisfiability problems. In
Proc.AAAI’92,pages 440–446. Copyright information
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