Aggregate meta-models for evolutionary multiobjective and many-objective optimization

@article{Pilt2013AggregateMF,
  title={Aggregate meta-models for evolutionary multiobjective and many-objective optimization},
  author={Martin Pil{\'a}t and Roman Neruda},
  journal={Neurocomputing},
  year={2013},
  volume={116},
  pages={392-402}
}
Evolutionary algorithms are among the best multiobjective optimizers. However, they need a large number of function evaluations. In this paper a meta-model based approach to the reduction in the needed number of function evaluations is presented. Local aggregate meta-models are used in a memetic operator. The algorithm is first discussed from a theoretical point of view and then it is shown that the meta-models greatly reduce the number of function evaluations. The approach is compared to a… CONTINUE READING
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