Online Interval Scheduling with Predictions

Joan Boyar, Lene M. Favrholdt, Shahin Kamali, Kim S. Larsen*


Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review


In online interval scheduling, the input is an online sequence of intervals, and the goal is to accept a maximum number of non-overlapping intervals. In the more general disjoint path allocation problem, the input is a sequence of requests, each involving a pair of vertices of a known graph, and the goal is to accept a maximum number of requests forming edge-disjoint paths between accepted pairs. These problems have been studied under extreme settings without information about the input or with error-free advice. We study an intermediate setting with a potentially erroneous prediction that specifies the set of intervals/requests forming the input sequence. For both problems, we provide tight upper and lower bounds on the competitive ratios of online algorithms as a function of the prediction error. For disjoint path allocation, our results rule out the possibility of obtaining a better competitive ratio than that of a simple algorithm that fully trusts predictions, whereas, for interval scheduling, we develop a superior algorithm. We also present asymptotically tight trade-offs between consistency (competitive ratio with error-free predictions) and robustness (competitive ratio with adversarial predictions) of interval scheduling algorithms. Finally, we provide experimental results on real-world scheduling workloads that confirm our theoretical analysis.
TitelAlgorithms and Data Structures : Proceedings of 18th International Symposium
RedaktørerPat Morin, Subhash Suri
ISBN (Trykt)9783031389054
StatusUdgivet - 2023
Begivenhed18th International Algorithms and Data Structures Symposium - Montreal, QC, Canada
Varighed: 31. jul. 20232. aug. 2023


Konference18th International Algorithms and Data Structures Symposium
ByMontreal, QC


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