Influence of selection and replacement strategies on linkage learning in BOA

@article{Lima2007InfluenceOS,
  title={Influence of selection and replacement strategies on linkage learning in BOA},
  author={C. Lima and M. Pelikan and D. Goldberg and F. Lobo and K. Sastry and Mark Hauschild},
  journal={2007 IEEE Congress on Evolutionary Computation},
  year={2007},
  pages={1083-1090}
}
  • C. Lima, M. Pelikan, +3 authors Mark Hauschild
  • Published 2007
  • Computer Science
  • 2007 IEEE Congress on Evolutionary Computation
  • The Bayesian optimization algorithm (BOA) uses Bayesian networks to learn linkages between the decision variables of an optimization problem. This paper studies the influence of different selection and replacement methods on the accuracy of linkage learning in BOA. Results on concatenated m-k deceptive trap functions show that the model accuracy depends on a large extent on the choice of selection method and to a lesser extent on the replacement strategy used. Specifically, it is shown that… CONTINUE READING
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