Let @math be a 3CNF formula with n variables and m clauses. A simple nonconstructive argument shows that when m is sufficiently large compared to n, most 3CNF formulas are not satisfiable. It is an open question whether there is an efficient refutation algorithm that for most such formulas proves that they are not satisfiable. A possible approach to refute a formula @math is: first, translate it into a graph @math using a generic reduction from 3-SAT to max-IS, then bound the maximum independent set of @math using the Lovasz @math function. If the @math function returns a value @math , this is a certificate for the unsatisfiability of @math . We show that for random formulas with @math clauses, the above approach fails, i.e. the @math function is likely to return a value of m.
A possible approach for refuting a formula @math is to find a resolution proof for the unsatisfiability of @math . However, Chvatal and Szemeredi @cite_5 proved that a resolution proof of a random 3CNF formula with linear number of clauses is almost surely of exponential size. A result of a similar flavor for denser formulas was given by Ben-Sasson and Wigderson @cite_8 who showed that a random formula with @math clauses almost surely requires a resolution proof of size @math . These lower bounds imply that finding a resolution proof for a random formula is computationally inefficient.
@cite_5 @cite_8
2000931246 2088616860
Let f be a random Boolean formula that is an instance of 3-SAT. We consider the problem of computing the least real number k such that if the ratio of the number of clauses over the number of variables of f strictly exceeds k , then f is almost certainly unsatisfiable. By a well-known and more or less straightforward argument, it can be shown that kF5.191. This upper bound was improved by to 4.758 by first providing new improved bounds for the occupancy problem. There is strong experimental evidence that the value of k is around 4.2. In this work, we define, in terms of the random formula f, a decreasing sequence of random variables such that, if the expected value of any one of them converges to zero, then f is almost certainly unsatisfiable. By letting the expected value of the first term of the sequence converge to zero, we obtain, by simple and elementary computations, an upper bound for k equal to 4.667. From the expected value of the second term of the sequence, we get the value 4.601q . In general, by letting the U This work was performed while the first author was visiting the School of Computer Science, Carleton Ž University, and was partially supported by NSERC Natural Sciences and Engineering Research Council . of Canada , and by a grant from the University of Patras for sabbatical leaves. The second and third Ž authors were supported in part by grants from NSERC Natural Sciences and Engineering Research . Council of Canada . During the last stages of this research, the first and last authors were also partially Ž . supported by EU ESPRIT Long-Term Research Project ALCOM-IT Project No. 20244 . †An extended abstract of this paper was published in the Proceedings of the Fourth Annual European Ž Symposium on Algorithms, ESA’96, September 25]27, 1996, Barcelona, Spain Springer-Verlag, LNCS, . pp. 27]38 . That extended abstract was coauthored by the first three authors of the present paper. Correspondence to: L. M. Kirousis Q 1998 John Wiley & Sons, Inc. CCC 1042-9832r98r030253-17 253 WC study the complexity of proving unsatisfiability for random k-CNP formulas with clause density A = m n where 111 is number of clauses and n is the number of variables. We prove the first nontrivial general upper bound, giving algorithmo that, in particular, for k = 3 produce refutations almost certainly in time 20t”iA). This is polynomial when