Optimal myopic algorithms for random 3-SAT

Let F/sub 3/(n, m) be a random 3-SAT formula formed by selecting uniformly, independently and with replacement, m clauses among all 8(/sup n/C/sub 3/) possible 3-clauses over n variables. It has been conjectured that there exists a constant r/sub 3/ such that, for any /spl epsiv/>0, F/sub 3/[n, (r/sub 3/-/spl epsiv/)n] is almost surely satisfiable, but F/sub 3/[n, (r/sub 3/+/spl epsiv/)n] is almost surely unsatisfiable. The best lower bounds for the potential value of r/sub 3/ have come form analyzing rather simple extensions of unit-clause propagation. It was shown by D. Achlioptas (2000) that all these extensions can be cast in a common framework and analyzed in a uniform manner by employing differential equations. We determine optimal algorithms that are expressible in that framework, establishing r/sub 3/>3. 26. We extend the analysis via differential equations, and make extensive use of a new optimization problem that we call the "max-density multiple-choice knapsack" problem. The structure of optimal knapsack solutions elegantly characterizes the choices made by an optimal algorithm.

Authors

• Dimitris Achlioptas
• Gregory B. Sorkin

Keywords

• Differential equations
• Computer science
• Mathematics
• Physics
• Upper bound
• Chaos
• Optimization Algorithm
• Myopic Algorithm
• Random 3-SAT
• Almost Surely
• Positive Probability
• Optimal Policy
• Convex Hull
• Lipschitz Continuous
• Line Balancing
• Knapsack Problem