Solving Problems with Unknown Solution Length at Almost No Extra Cost

@article{Doerr2018SolvingPW,
  title={Solving Problems with Unknown Solution Length at Almost No Extra Cost},
  author={Benjamin Doerr and Carola Doerr and Timo K{\"o}tzing},
  journal={Algorithmica},
  year={2018},
  pages={1-46}
}
Following up on previous work of Cathabard et al. (in: Proceedings of foundations of genetic algorithms (FOGA’11), ACM, 2011) we analyze variants of the (1 + 1) evolutionary algorithm (EA) for problems with unknown solution length. For their setting, in which the solution length is sampled from a geometric distribution, we provide mutation rates that yield for both benchmark functions OneMax and LeadingOnes an expected optimization time that is of the same order as that of the (1 + 1) EA… CONTINUE READING

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