A Complexity Index for Satisfiability Problems
SIAM Journal on Computing
Investigations on autark assignments
Discrete Applied Mathematics - Special issue on Boolean functions and related problems
Solving satisfiability problems using elliptic approximations - effective branching rules
Discrete Applied Mathematics - Special issue on Boolean functions and related problems
Results related to threshold phenomena research in satisfiability: lower bounds
Theoretical Computer Science - Phase transitions in combinatorial problems
Lower bounds for random 3-SAT via differential equations
Theoretical Computer Science - Phase transitions in combinatorial problems
The Probabilistic Analysis of a Greedy Satisfiability Algorithm
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Lean clause-sets: generalizations of minimally unsatisfiable clause-sets
Discrete Applied Mathematics - The renesse issue on satisfiability
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We introduce two incomplete polynomial time algorithms to solve satisfiability problems which both use Linear Programming (LP) techniques. First, the FlipFlop LP attempts to simulate a Quadratic Program which would solve the CNF at hand. Second, the WeightedLinearAutarky LP is an extended variant of the LinearAutarky LP as defined by Kullmann [6] and iteratively updates its weights to find autarkies in a given formula. Besides solving satisfiability problems, this LP could also be used to study the existence of autark assignments in formulas. Results within the experimental domain (up to 1000 variables) show a considerably sharper lower bound for the uniform random 3-Sat phase transition density than the proved lower bound of the myopic algorithm ( 3.26) by Achlioptas [1] and even than that of the greedy algorithm ( 3.52) proposed by Kaporis [5].