@InProceedings{mullerhannemann_et_al:OASIcs.ATMOS.2021.3,
  author =	{M\"{u}ller-Hannemann, Matthias and R\"{u}ckert, Ralf and Schiewe, Alexander and Sch\"{o}bel, Anita},
  title =	{{Towards Improved Robustness of Public Transport by a Machine-Learned Oracle}},
  booktitle =	{21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)},
  pages =	{3:1--3:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-213-6},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{96},
  editor =	{M\"{u}ller-Hannemann, Matthias and Perea, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.3},
  URN =		{urn:nbn:de:0030-drops-148721},
  doi =		{10.4230/OASIcs.ATMOS.2021.3},
  annote =	{Keywords: Public Transportation, Timetabling, Machine Learning, Robustness}
}