| Article ID: | iaor19972074 |
| Country: | United States |
| Volume: | 8 |
| Issue: | 2 |
| Start Page Number: | 183 |
| End Page Number: | 191 |
| Publication Date: | Apr 1996 |
| Journal: | INFORMS Journal On Computing |
| Authors: | Koehler Gary J., Aytug Haldun |
| Keywords: | genetic algorithms |
Considerable empirical results have been reported on the computational performance of genetic algorithms but little has been studied on their convergence behavior or on stopping criteria. In this paper the authors derive bounds on the number of iterations required to achieve a level of confidence to guarantee that a genetic algorithm has seen all populations and, hence, an optimal solution.