ML Anthology

Equitable Scheduling on a Single Machine

Klaus Heeger, Danny Hermelin, George B. Mertzios, Hendrik Molter, Rolf Niedermeier, Dvir Shabtay
AAAI 2021 pp. 11818-11825
doi:10.1609/AAAI.V35I13.17404 /aaai/2021/heeger2021aaai-equitable/

Abstract

We introduce a natural but seemingly yet unstudied generalization of the problem of scheduling jobs on a single machine so as to minimize the number of tardy jobs. Our generalization lies in simultaneously considering several instances of the problem at once. In particular, we have n clients over a period of m days, where each client has a single job with its own processing time and deadline per day. Our goal is to provide a schedule for each of the m days, so that each client is guaranteed to have their job meet its deadline in at least k

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Text

Heeger et al. "Equitable Scheduling on a Single Machine." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I13.17404

Markdown

[Heeger et al. "Equitable Scheduling on a Single Machine." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/heeger2021aaai-equitable/) doi:10.1609/AAAI.V35I13.17404

BibTeX

@inproceedings{heeger2021aaai-equitable,
  title     = {{Equitable Scheduling on a Single Machine}},
  author    = {Heeger, Klaus and Hermelin, Danny and Mertzios, George B. and Molter, Hendrik and Niedermeier, Rolf and Shabtay, Dvir},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {11818-11825},
  doi       = {10.1609/AAAI.V35I13.17404},
  url       = {https://mlanthology.org/aaai/2021/heeger2021aaai-equitable/}
}