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International Conference on Combinatorial Optimization and Applications

COCOA 2014: Combinatorial Optimization and Applications pp 3–12Cite as

An Exact Algorithm for Non-preemptive Peak Demand Job Scheduling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8881))

Abstract

Peak demand scheduling aims to schedule jobs so as to minimize the peak load in the schedule. An important application of this problem comes from scheduling power jobs in the smart grid. Currently, peaks in power demand are due to the aggregation of many jobs being scheduled in an on-demand fashion. Often these have some flexibility in their starting times which can be leveraged to lower the peak demand of a schedule. While the general version of the problem is known to be NP-hard (we observe it is even NP-hard to approximate), we provide an optimal algorithm based on dynamic programming that is fixed-parameter tractable (FPT). Simulation results using household power usage data show that peak power demand can be significantly reduced by allowing some flexibility in job execution times and applying scheduling.

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Notes

  1. 1.

    While not explicitly stated in [16], the best approximation ratio achieved for the MP algorithm results from minimizing \(a + 2 + \frac{2a}{a-1}\), which occurs at \(a = \sqrt{2} + 1\) and yields an approximation ratio of \(7.82\).

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Author information

Authors and Affiliations

  1. Department of Computer Science, Montana State University, Bozeman, MT, USA

    Sean Yaw & Brendan Mumey

Authors
  1. Sean Yaw
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  2. Brendan Mumey
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Corresponding author

Correspondence to Sean Yaw .

Editor information

Editors and Affiliations

  1. Zhejiang Normal University, Jinhua, Zhejiang, China

    Zhao Zhang

  2. University of Texas, Tyler, Texas, USA

    Lidong Wu

  3. University of Texas, Dallas, Texas, USA

    Wen Xu

  4. University of Texas, Dallas, USA

    Ding-Zhu Du

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Yaw, S., Mumey, B. (2014). An Exact Algorithm for Non-preemptive Peak Demand Job Scheduling. In: Zhang, Z., Wu, L., Xu, W., Du, DZ. (eds) Combinatorial Optimization and Applications. COCOA 2014. Lecture Notes in Computer Science(), vol 8881. Springer, Cham. https://doi.org/10.1007/978-3-319-12691-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-12691-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12690-6

  • Online ISBN: 978-3-319-12691-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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