| Article ID: | iaor19991397 |
| Country: | Netherlands |
| Volume: | 96 |
| Issue: | 1 |
| Start Page Number: | 195 |
| End Page Number: | 201 |
| Publication Date: | Jan 1997 |
| Journal: | European Journal of Operational Research |
| Authors: | Koehler Gary J., Aytug Haldun, Bhattacharrya Siddartha |
| Keywords: | genetic algorithms |
In this paper we model the run time behaviour of GAs using higher cardinality representations as Markov Chains, define the states of the Markov Chain and derive the transition probabilities of the corresponding transition matrix. We analyze the behavior of this chain and obtain bounds on its convergence rate and bounds on the runtime complexity of the GA. We further investigate the effects of using binary versus higher cardinality representation of a search space.