Selecting Complementary Pairs of Literals

Abstract We present and rigorously analyze a heuristic that searches for a satisfying truth assignment of a given random instance of the 3-SAT problem. We prove that the heuristic asymptotically certainly succeeds in producing a satisfying truth assignment for formulas with clauses to variables ratio (density) of up to 3.52. Thus the experimentally observed threshold of the density where a typical formula's phase changes from asymptotically certainly satisfiable to asymptotically certainly contradictory is rigorously shown to be at least 3.52. The best previous lower bound in the long series of mathematically rigorous approximations by various research groups of the experimental threshold was 3.42. That was the first result where the probabilistic analysis was based on random formulas with a pre-specified, typical number of appearances for each literal. However, in that result, in order to simplify the analysis, the number of appearances of each literal was decoupled from the number of appearances of its negation. In this work, we assume not only that each literal has the typical number of occurrences, but that for each variable both numbers of occurrences of its positive and negated appearances are typical. By standard techniques, our algorithm can be easily modified to run in linear time. Thus not only the satisfiability threshold, but also the threshold (experimental again) where the complexity of searching for satisfying truth assignments jumps from polynomial to exponential is at least 3.52. This should be contrasted with the value 3.9 for the complexity threshold given by theoretical (but not mathematically rigorous) techniques of Statistical Physics.

[1]  Dimitris Achlioptas,et al.  Setting 2 variables at a time yields a new lower bound for random 3-SAT (extended abstract) , 1999, STOC '00.

[2]  E. Friedgut,et al.  Sharp thresholds of graph properties, and the -sat problem , 1999 .

[3]  L. Kirousis,et al.  Approximating the unsatisfiability threshold of random formulas , 1998 .

[4]  Alan M. Frieze,et al.  Analysis of Two Simple Heuristics on a Random Instance of k-SAT , 1996, J. Algorithms.

[5]  Bruce A. Reed,et al.  Mick gets some (the odds are on his side) (satisfiability) , 1992, Proceedings., 33rd Annual Symposium on Foundations of Computer Science.

[6]  N. Wormald Differential Equations for Random Processes and Random Graphs , 1995 .

[7]  David S. Johnson,et al.  Approximation algorithms for combinatorial problems , 1973, STOC.

[8]  Yacine Boufkhad,et al.  A General Upper Bound for the Satisfiability Threshold of Random r-SAT Formulae , 1997, J. Algorithms.

[9]  John V. Franco Results related to threshold phenomena research in satisfiability: lower bounds , 2001, Theor. Comput. Sci..

[10]  M. Mézard,et al.  Random K-satisfiability problem: from an analytic solution to an efficient algorithm. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  Lefteris M. Kirousis,et al.  The probabilistic analysis of a greedy satisfiability algorithm , 2002, Random Struct. Algorithms.

[12]  Dimitris Achlioptas,et al.  Lower bounds for random 3-SAT via differential equations , 2001, Theor. Comput. Sci..

[13]  Yannis C. Stamatiou,et al.  The unsatisfiability threshold revisited , 2001, Electron. Notes Discret. Math..

[14]  Olivier Dubois,et al.  Typical random 3-SAT formulae and the satisfiability threshold , 2000, SODA '00.

[15]  Wenceslas Fernandez de la Vega,et al.  On Random 3-sat , 1995, Comb. Probab. Comput..

[16]  Alan M. Frieze,et al.  A note on random 2-SAT with prescribed literal degrees , 2002, SODA '02.

[17]  Gilles Dequen,et al.  A backbone-search heuristic for efficient solving of hard 3-SAT formulae , 2001, IJCAI.

[18]  Dimitris Achlioptas,et al.  Optimal myopic algorithms for random 3-SAT , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[19]  Ming-Te Chao,et al.  Probabilistic analysis of a generalization of the unit-clause literal selection heuristics for the k satisfiability problem , 1990, Inf. Sci..

[20]  Michael Molloy,et al.  The Probabilistic Method , 1998 .

[21]  M. Mézard,et al.  Analytic and Algorithmic Solution of Random Satisfiability Problems , 2002, Science.

[22]  Cristopher Moore,et al.  The asymptotic order of the random k-SAT threshold , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..

[23]  Alan M. Frieze,et al.  On the satisfiability and maximum satisfiability of random 3-CNF formulas , 1993, SODA '93.

[24]  Luc Devroye,et al.  Branching Processes and Their Applications in the Analysis of Tree Structures and Tree Algorithms , 1998 .

[25]  Andreas Goerdt A Threshold for Unsatisfiability , 1996, J. Comput. Syst. Sci..

[26]  M. Mitzenmacher Tight Thresholds for The Pure Literal Rule , 1997 .

[27]  Ming-Te Chao,et al.  Probabilistic Analysis of Two Heuristics for the 3-Satisfiability Problem , 1986, SIAM J. Comput..

[28]  S. Janson,et al.  Bounding the unsatisfiability threshold of random 3-SAT , 2000 .