Scheduling with Speed Predictions. (arXiv:2205.01247v1 [cs.DS])

Web: http://arxiv.org/abs/2205.01247

Algorithms with predictions is a recent framework that has been used to
overcome pessimistic worst-case bounds in incomplete information settings. In
the context of scheduling, very recent work has leveraged machine-learned
predictions to design algorithms that achieve improved approximation ratios in
settings where the processing times of the jobs are initially unknown. In this
paper, we study the speed-robust scheduling problem where the speeds of the
machines, instead of the processing times of the jobs, are unknown and augment
this …

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