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Time-of-Use Scheduling Problem with Equal-Length Jobs

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Theory and Applications of Models of Computation (TAMC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13571))

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Abstract

In this paper, we study the scheduling problem recently introduced by Wan and Qi [NRL’2010]. We are given a set of jobs to be scheduled on a single machine, in which the cost of scheduling a job depends on when it is scheduled. This model is also known as Time-of-Use tariff. Each job is defined by its release time, its deadline and its processing time. The goal is to schedule the maximum number of jobs such that the total cost does not exceed a given budget. The problem is NP-hard when jobs have arbitrary processing time. However, when jobs have the same processing time, we show that the problem can be solved in polynomial time via dynamic programming techniques. In addition, we consider the case in which jobs have agreeable deadline, and we provide a faster algorithm.

This work is supported by the national key research and development program of China under grant No 2019YFB2102200, and by the Fundamental Research Funds for the Central Universities No 2242022R10024.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Southeast University, Nanjing, China

    Vincent Chau, Chenchen Fu, Yan Lyu, Weiwei Wu & Yizheng Zhang

Authors
  1. Vincent Chau
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  2. Chenchen Fu
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  3. Yan Lyu
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  4. Weiwei Wu
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  5. Yizheng Zhang
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Corresponding author

Correspondence to Yizheng Zhang .

Editor information

Editors and Affiliations

  1. University of Texas at Dallas, Richardson, TX, USA

    Ding-Zhu Du

  2. University of New Brunswick, Fredericton, NB, Canada

    Donglei Du

  3. Tianjin University of Technology, Tianjin, China

    Chenchen Wu

  4. Beijing University of Technology, Beijing, China

    Dachuan Xu

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Chau, V., Fu, C., Lyu, Y., Wu, W., Zhang, Y. (2022). Time-of-Use Scheduling Problem with Equal-Length Jobs. In: Du, DZ., Du, D., Wu, C., Xu, D. (eds) Theory and Applications of Models of Computation. TAMC 2022. Lecture Notes in Computer Science, vol 13571. Springer, Cham. https://doi.org/10.1007/978-3-031-20350-3_3

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  • DOI: https://doi.org/10.1007/978-3-031-20350-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20349-7

  • Online ISBN: 978-3-031-20350-3

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