English

A Fixed-Parameter Algorithm for Random Instances of Weighted d-CNF Satisfiability

Data Structures and Algorithms 2008-12-18 v1 Artificial Intelligence Computational Complexity

Abstract

We study random instances of the weighted dd-CNF satisfiability problem (WEIGHTED dd-SAT), a generic W[1]-complete problem. A random instance of the problem consists of a fixed parameter kk and a random dd-CNF formula \weicnfnpk,d\weicnf{n}{p}{k, d} generated as follows: for each subset of dd variables and with probability pp, a clause over the dd variables is selected uniformly at random from among the 2d12^d - 1 clauses that contain at least one negated literals. We show that random instances of WEIGHTED dd-SAT can be solved in O(k2n+nO(1))O(k^2n + n^{O(1)})-time with high probability, indicating that typical instances of WEIGHTED dd-SAT under this instance distribution are fixed-parameter tractable. The result also hold for random instances from the model \weicnfnpk,d(d)\weicnf{n}{p}{k,d}(d') where clauses containing less than d(1<d<d)d' (1 < d' < d) negated literals are forbidden, and for random instances of the renormalized (miniaturized) version of WEIGHTED dd-SAT in certain range of the random model's parameter p(n)p(n). This, together with our previous results on the threshold behavior and the resolution complexity of unsatisfiable instances of \weicnfnpk,d\weicnf{n}{p}{k, d}, provides an almost complete characterization of the typical-case behavior of random instances of WEIGHTED dd-SAT.

Keywords

Cite

@article{arxiv.0806.4652,
  title  = {A Fixed-Parameter Algorithm for Random Instances of Weighted d-CNF Satisfiability},
  author = {Yong Gao},
  journal= {arXiv preprint arXiv:0806.4652},
  year   = {2008}
}

Comments

13 pages

R2 v1 2026-06-21T10:55:19.430Z