A fast, purely deterministic solver for a subset of 3SAT problems. This algorithm uses frequency-based greedy variable assignment to find satisfying solutions in polynomial time.
| M/N Ratio | Success Rate | Use Case |
|---|---|---|
| 1.0 | ~99% | Under-constrained |
| 2.0 | ~83% | Typical instances |
| 4.2 | ~40%-50% | Phase transition (hardest) |
| 10.0+ | Variable | Over-constrained |
- Time Complexity: Polynomial time O(MN) vs exponential for complete solvers
- Success Rate: 40-99% depending on problem structure
- Speed: Solves most instances in microseconds
- Memory: O(M+N) space complexity
- Best Performance: Under-constrained instances (M/N < 3)
- Under-constrained problems (M/N < 3)
- Quick first-pass attempts
- Real-time applications requiring fast responses
- Preprocessing step before expensive solvers
- Problems requiring completeness guarantees
- Adversarially constructed instances
- Phase transition region problems (unless speed > accuracy)
- Incomplete: Cannot solve all satisfiable instances
- No backtracking: May get stuck in local optima
- No clause learning: Doesn't learn from conflicts