Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution

@article{Li2019WhichSW,
  title={Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution},
  author={Ke Li and Zilin Xiang and Kathryn C B Tan},
  journal={2019 IEEE Congress on Evolutionary Computation (CEC)},
  year={2019},
  pages={1988-1995}
}
It is not uncommon that meta-heuristic algorithms contain some intrinsic parameters, the optimal configuration of which is crucial for achieving their peak performance. However, evaluating the effectiveness of a configuration is expensive, as it involves many costly runs of the target algorithm. Perhaps surprisingly, it is possible to build a cheap-to-evaluate surrogate that models the algorithm’s empirical performance as a function of its parameters. Such surrogates constitute an important… CONTINUE READING

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