Research map / Learning theory and algorithms / Combinatorial and search optimization
Improved Algorithms for Maximum Satisfiability and Its Special Cases
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the improved branching and reduction rules for (n, 3)-MAXSAT | (n, 3)-MAXSAT · (n, 3)-MAXSAT | running time: O∗(1.191n) -> O∗(1.1749n) | Helped |
| Use the improved branching and reduction rules for (n, 4)-MAXSAT | (n, 4)-MAXSAT · (n, 4)-MAXSAT | running time: O∗(1.4254n) -> O∗(1.3803n) | Helped |
| Use the improved bounded-occurrence algorithms to solve general MAXSAT | MAXSAT · MAXSAT | running time: O∗(1.0927L) -> O∗(1.0911L) | Helped |
| Use the algorithm in terms of k for (n, 3)-MAXSAT | (n, 3)-MAXSAT · (n, 3)-MAXSAT | running time: O∗(1.1554k) | Helped |
| Use the algorithm in terms of k for (n, 4)-MAXSAT | (n, 4)-MAXSAT · (n, 4)-MAXSAT | running time: O∗(1.2989k) | Helped |
| Use the discounted-length measure instead of measuring complexity only by formula length | The MAXSAT algorithm · MAXSAT | running time: O∗(1.08391d), O∗(1.08391L), O∗(1.0911d), O∗(1.0911L) | Helped |
Closest papers by meaning
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