# Scheduling Jobs with Stochastic Holding Costs

@inproceedings{Lee2021SchedulingJW, title={Scheduling Jobs with Stochastic Holding Costs}, author={Dabeen Lee and Milan Vojnovic}, year={2021} }

This paper proposes a learning and scheduling algorithm to minimize the expected cumulative holding cost incurred by jobs, where statistical parameters defining their individual holding costs are unknown a priori. In each time slot, the server can process a job while receiving the realized random holding costs of the jobs remaining in the system. Our algorithm is a learning-based variant of the cμ rule for scheduling: it starts with a preemption period of fixed length which serves as a learning…

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