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

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 t...

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Bibliographic Details
Published in:Annals of operations research 2016-03, Vol.238 (1-2), p.199-227
Main Authors: Fang, Kan, Uhan, Nelson A., Zhao, Fu, Sutherland, John W.
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Business and Management
Combinatorics
Computer science
Cost control
Demand
Electric power generation
Electricity
Electricity pricing
Employment
Energy consumption
Energy prices
Energy use
Industrial equipment
Integer programming
Job shops
Manufacturing
Mathematical analysis
Mathematical models
Methods
Operations research
Operations Research/Decision Theory
Polynomials
Production scheduling
Properties
Release dates
Scheduling
Scheduling (Management)
Studies
Tariffs
Theory of Computation
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Summary: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 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.
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-015-2003-5