A Reduced Markov Model of GAs Without the Exact Transition Matrix

@inproceedings{Moey2004ARM,
  title={A Reduced Markov Model of GAs Without the Exact Transition Matrix},
  author={Cheah C. J. Moey and Jonathan E. Rowe},
  booktitle={PPSN},
  year={2004}
}
Modelling a finite population genetic algorithm (GA) as a Markov chain can quickly become unmanageable since the number of population states increases rapidly with the population size and search space size. One approach to resolving this issue is to “lump” similar states together, so that a tractable Markov chain can be produced. A paper by Spears and De Jong in [1] presents an algorithm that can be used to lump states together, thus compressing the probability transition matrix. However, to… CONTINUE READING

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