Benchmarking Numerical Multiobjective Optimizers Revisited

@inproceedings{Brockhoff2015BenchmarkingNM,
  title={Benchmarking Numerical Multiobjective Optimizers Revisited},
  author={Dimo Brockhoff and Thanh-Do Tran and Nikolaus Hansen},
  booktitle={GECCO},
  year={2015}
}
Algorithm benchmarking plays a vital role in designing new optimization algorithms and in recommending efficient and robust algorithms for practical purposes. So far, two main approaches have been used to compare algorithms in the evolutionary multiobjective optimization (EMO) field: (i) displaying empirical attainment functions and (ii) reporting statistics on quality indicator values. Most of the time, EMO benchmarking studies compare algorithms for fixed and often arbitrary budgets of… CONTINUE READING
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