Statistical distribution of the convergence time of evolutionary algorithms for long-path problems

@article{Garnier2000StatisticalDO,
  title={Statistical distribution of the convergence time of evolutionary algorithms for long-path problems},
  author={Josselin Garnier and Leila Kallel},
  journal={IEEE Trans. Evolutionary Computation},
  year={2000},
  volume={4},
  pages={16-30}
}
| The behavior of a (1+1)-ES process on Rudolph's binary long k-paths is investigated extensively in the asymptotic framework with respect to string length l. First, the case of k = l is addressed. For 1=2, we prove that the long k-path is a longpath for the (1+1)-ES, in the sense that the process follows the entire path with no shortcuts resulting in an exponential expected convergence time. For < 1=2, the expected convergence time is also exponential but some shortcuts occur meanwhile that… CONTINUE READING

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