Scheduling on a single machine under time-of-use electricity tariffs

Kan Fang (), Nelson Uhan (), Fu Zhao () and John Sutherland ()

Annals of Operations Research, 2016, vol. 238, issue 1, 199-227

Abstract: We consider the problem of scheduling jobs on a single machine to minimize the total electricity cost of processing these jobs under time-of-use electricity tariffs. For the uniform-speed case, in which all jobs have arbitrary power demands and must be processed at a single uniform speed, we prove that the non-preemptive version of this problem is inapproximable within a constant factor unless $$\text {P}=\text {NP}$$ P = NP . On the other hand, when all the jobs have the same workload and the electricity prices follow a so-called pyramidal structure, we show that this problem can be solved in polynomial time. For the speed-scalable case, in which jobs can be processed at an arbitrary speed with a trade-off between speed and power demand, we show that the non-preemptive version of the problem is strongly NP-hard. We also present different approximation algorithms for this case, and test the computational performance of these approximation algorithms on randomly generated instances. In addition, for both the uniform-speed and speed-scaling cases, we show how to compute optimal schedules for the preemptive version of the problem in polynomial time. Copyright Springer Science+Business Media New York (outside the USA) 2016

Keywords: Scheduling; Time-of-use tariff; Electricity cost; Dynamic speed scaling; Approximation algorithm (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (20)

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DOI: 10.1007/s10479-015-2003-5

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