@inproceedings{46305,
  abstract     = {{Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.}},
  author       = {{Rook, J and Trautmann, Heike and Bossek, Jakob and Grimme, C}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  editor       = {{Fieldsend, J and Wagner, M.}},
  isbn         = {{9781450392686}},
  pages        = {{356–359}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}}},
  doi          = {{10.1145/3520304.3528998}},
  year         = {{2022}},
}