Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Non-Clairvoyant Makespan Minimization Scheduling with Predictions. / Bampis, Evripidis; Кононов, Александр Вениаминович; Lucarelli, Giorgio и др.
Leibniz International Proceedings in Informatics, LIPIcs. Том 283 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2023. 9 (Leibniz International Proceedings in Informatics, LIPIcs; Том 283).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Non-Clairvoyant Makespan Minimization Scheduling with Predictions
AU - Bampis, Evripidis
AU - Кононов, Александр Вениаминович
AU - Lucarelli, Giorgio
AU - Pascual, Fanny
N1 - Conference code: 34
PY - 2023/12
Y1 - 2023/12
N2 - We revisit the classical non-clairvoyant problem of scheduling a set of n jobs on a set of m parallel identical machines where the processing time of a job is not known until the job finishes. Our objective is the minimization of the makespan, i.e., the date at which the last job terminates its execution. We adopt the framework of learning-augmented algorithms and we study the question of whether (possibly erroneous) predictions may help design algorithms with a competitive ratio which is good when the prediction is accurate (consistency), deteriorates gradually with respect to the prediction error (smoothness), and not too bad and bounded when the prediction is arbitrarily bad (robustness). We first consider the non-preemptive case and we devise lower bounds, as a function of the error of the prediction, for any deterministic learning-augmented algorithm. Then we analyze a variant of Longest Processing Time first (LPT) algorithm (with and without release dates) and we prove that it is consistent, smooth, and robust. Furthermore, we study the preemptive case and we provide lower bounds for any deterministic algorithm with predictions as a function of the prediction error. Finally, we introduce a variant of the classical Round Robin algorithm (RR), the Predicted Proportional Round Robin algorithm (PPRR), which we prove to be consistent, smooth and robust.
AB - We revisit the classical non-clairvoyant problem of scheduling a set of n jobs on a set of m parallel identical machines where the processing time of a job is not known until the job finishes. Our objective is the minimization of the makespan, i.e., the date at which the last job terminates its execution. We adopt the framework of learning-augmented algorithms and we study the question of whether (possibly erroneous) predictions may help design algorithms with a competitive ratio which is good when the prediction is accurate (consistency), deteriorates gradually with respect to the prediction error (smoothness), and not too bad and bounded when the prediction is arbitrarily bad (robustness). We first consider the non-preemptive case and we devise lower bounds, as a function of the error of the prediction, for any deterministic learning-augmented algorithm. Then we analyze a variant of Longest Processing Time first (LPT) algorithm (with and without release dates) and we prove that it is consistent, smooth, and robust. Furthermore, we study the preemptive case and we provide lower bounds for any deterministic algorithm with predictions as a function of the prediction error. Finally, we introduce a variant of the classical Round Robin algorithm (RR), the Predicted Proportional Round Robin algorithm (PPRR), which we prove to be consistent, smooth and robust.
KW - learning-augmented algorithm
KW - online
KW - scheduling
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85179131991&origin=inward&txGid=053c894a99a86df633cb673571904538
UR - https://www.mendeley.com/catalogue/20eb4734-dda3-3682-bf55-a92eb6ae505e/
U2 - 10.4230/LIPIcs.ISAAC.2023.9
DO - 10.4230/LIPIcs.ISAAC.2023.9
M3 - Conference contribution
SN - 978-395977289-1
VL - 283
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - Leibniz International Proceedings in Informatics, LIPIcs
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 34th International Symposium on Algorithms and Computation
Y2 - 3 December 2023 through 6 December 2023
ER -
ID: 59356328