We study the scheduling problem with calibrations. We are given a set of n jobs that need to be scheduled on a set of m machines. However, a machine can schedule jobs only if a calibration has been performed beforehand and the machine is considered as valid during a fixed time period of T, after which it must be recalibrated before running more jobs. In this paper, we investigate the batch calibrations, calibrations occur in batch and at the same moment. It is then not possible to perform any calibrations during a period of T. We consider different cost function depending on the number of machines we calibrate at a given time. Moreover, jobs have release time, deadline and unit processing time. The objective is to schedule all jobs with the minimum cost of calibrations. We give a dynamic programming to solve the case with arbitrary cost function. Then, we propose several faster approximation algorithm for different cost function.
CITATION STYLE
Chau, V., Li, M., Wang, Y., Zhang, R., & Zhao, Y. (2019). Minimizing the Cost of Batch Calibrations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11653 LNCS, pp. 78–89). Springer Verlag. https://doi.org/10.1007/978-3-030-26176-4_7
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