Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments

@inproceedings{PrgelBennett2015RunTimeAO,
  title={Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments},
  author={Adam Pr{\"u}gel-Bennett and Jonathan E. Rowe and Jonathan L. Shapiro},
  booktitle={FOGA},
  year={2015}
}
This paper analyses a generational evolutionary algorithm using only selection and uniform crossover. With a probability arbitrarily close to one the evolutionary algorithm is shown to solve onemax in <i>O</i>(<i>n</i> log<sup>2</sup>(<i>n</i>)) function evaluations using a population of size <i>c</i>,<i>n</i>, log(<i>n</i>). We then show that this algorithm can solve onemax with noise variance <i>n</i> again in <i>O</i>(<i>n</i> log<sup>2</sup>(<i>n</i>)) function evaluations. 

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