A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA

Anton Bouter, Peter A. N. Bosman. A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA. In Sara Silva, Luís Paquete, editors, Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023. pages 1864-1872, ACM, 2023. [doi]

@inproceedings{BouterB23,
  title = {A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA},
  author = {Anton Bouter and Peter A. N. Bosman},
  year = {2023},
  doi = {10.1145/3583133.3596361},
  url = {https://doi.org/10.1145/3583133.3596361},
  researchr = {https://researchr.org/publication/BouterB23},
  cites = {0},
  citedby = {0},
  pages = {1864-1872},
  booktitle = {Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023},
  editor = {Sara Silva and Luís Paquete},
  publisher = {ACM},
}