• DOI:10.1109/SFFCS.1999.814612
• Corpus ID: 123177576

A probabilistic algorithm for k-SAT and constraint satisfaction problems

@article{Schoning1999APA,
  title={A probabilistic algorithm for k-SAT and constraint satisfaction problems},
  author={Torsten Schoning},
  journal={40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039)},
  year={1999},
  pages={410-414}
}

• T. Schoning
• Published 17 October 1999
• Computer Science
• 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039)

We present a simple probabilistic algorithm for solving k-SAT and more generally, for solving constraint satisfaction problems (CSP). The algorithm follows a simple local search paradigm (S. Minton et al., 1992): randomly guess an initial assignment and then, guided by those clauses (constraints) that are not satisfied, by successively choosing a random literal from such a clause and flipping the corresponding bit, try to find a satisfying assignment. If no satisfying assignment is found after O(n) steps, start over again. Our analysis shows that for any satisfiable k-CNF-formula with n variables this process has to be repeated only t times, on the average, to find a satisfying assignment, where t is within a polynomial factor of (2(1-1/k))/sup n/. This is the fastest (and also the simplest) algorithm for 3-SAT known up to date. We consider also the more general case of a CSP with n variables, each variable taking at most d values, and constraints of order l, and analyze the complexity of the corresponding (generalized) algorith m. It turns out that any CSP can be solved with complexity at most (d/spl middot/(1-1/l)+/spl epsiv/)/sup n/.