Develops O(1)-competitive learning-augmented scheduling algorithms with O(1) preemptions per job for single and unrelated machines, with logarithmic overhead on prediction error, and first such guarantees for unrelated and malleable machines.
The targeted processing requirement for each job j∈J k is thenv j,k = min{uj,k, lky(k) j }
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Learning-Augmented Online Scheduling with Parsimonious Preemption
Develops O(1)-competitive learning-augmented scheduling algorithms with O(1) preemptions per job for single and unrelated machines, with logarithmic overhead on prediction error, and first such guarantees for unrelated and malleable machines.