Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
| Hi-index | 0.00 |
A general model of local improvement algorithms in combinatorial optimization accurately confirms performance characteristics often observed in individual cases. The model predicts exponentially bad worst case and low order polynomial average run times for single optimum problems including some linear complementarity problems and linear programming. For problems with multiple local optima, most notably those that are NP-complete, average speed is linearly bounded but accuracy is poor.