Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones

@inproceedings{Doerr2018TowardsAT,
  title={Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones},
  author={Carola Doerr and Furong Ye and Sander van Rijn and H. J. Wang and Thomas B{\"a}ck},
  booktitle={GECCO},
  year={2018}
}
Theoretical and empirical research on evolutionary computation methods complement each other by providing two fundamentally different approaches towards a better understanding of black-box optimization heuristics. In discrete optimization, both streams developed rather independently of each other, but we observe today an increasing interest in reconciling these two sub-branches. In continuous optimization, the COCO (Comparing Continuous Optimisers) benchmarking suite has established itself as… CONTINUE READING