Convergence Properties of Optimization Algorithms for the SAT Problem

  • Authors:
  • Jun Gu;Qian-Ping Gu;Ding-Zhu Du

  • Affiliations:
  • -;-;-

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1996

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Abstract

The satisfiability (SAT) problem is a basic problem in computing theory. Presently, an active area of research on SAT problem is to design efficient algorithms to find a solution for a satisfiable conjunctive normal form (CNF) formula. A new formulation, the Universal SAT problem model, which transforms the SAT problem on Boolean space into an optimization problem on real space has been developed [27], [28], [30]. Many optimization techniques, such as the steepest descent method, Newton's method, and the coordinate descent method, can be used to solve the Universal SAT problem. In this paper, we prove that, when the initial solution is sufficiently close to the optimal solution, the steepest descent method has a linear convergence ratio β