Article ID: | iaor20084673 |
Country: | Netherlands |
Volume: | 178 |
Issue: | 1 |
Start Page Number: | 27 |
End Page Number: | 45 |
Publication Date: | Apr 2007 |
Journal: | European Journal of Operational Research |
Authors: | Koehler Gary J., Aytu Haldun |
Keywords: | markov processes, computational analysis |
Genetic algorithms are stochastic search algorithms that have been applied to optimization problems. In this paper we analyze the run-time complexity of a genetic algorithm when we are interested in one of a set of distinguished solutions. One such case occurs when multiple optima exist. We define the worst case scenario and derive a probabilistic worst case bound on the number of iterations required to find one of these multiple solutions of interest.