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Parallel Machine Scheduling with a Single Server: Loading and Unloading

  • Conference paper
Combinatorial Optimization and Applications (COCOA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8287))

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Abstract

This paper addresses the non-preemptive scheduling on two parallel identical machines sharing a single server in charge of loading and unloading jobs. Each job has to be loaded by the server before being processed on one of the machines and unloaded immediately by the server after its processing. The goal is to minimize the makespan. This paper considers classical algorithms LS and LPT for the problem where the loading and unloading times both are equal to one time unit. We first analyze the structure of list scheduling for the problem and then show that the tight worst case ratios of LS and LPT are 12/7 and 4/3, respectively. Finally, we provide a proof of computational complexity for the problem.

Supported by the National Natural Science Foundation of China (11001242, 11071220) and Zhejiang Province Natural Science Foundation of China (LY13A010015).

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Author information

Authors and Affiliations

  1. Department of Mathematics, Zhejiang Sci-Tech University, Hangzhou, 310018, China

    Jueliang Hu, Qinghui Zhang, Jianming Dong & Yiwei Jiang

Authors
  1. Jueliang Hu
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  2. Qinghui Zhang
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  3. Jianming Dong
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  4. Yiwei Jiang
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Editor information

Editors and Affiliations

  1. Institute of Theoretical Computer Science, ETH Zürich, Zürich, Switzerland

    Peter Widmayer

  2. State Key Lab for Manufacturing Systems Engineering, 710049, Xi’an, China

    Yinfeng Xu

  3. Department of Computer Science, Montana State University, 59717-3880, Bozeman, MT, USA

    Binhai Zhu

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© 2013 Springer International Publishing Switzerland

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Hu, J., Zhang, Q., Dong, J., Jiang, Y. (2013). Parallel Machine Scheduling with a Single Server: Loading and Unloading. In: Widmayer, P., Xu, Y., Zhu, B. (eds) Combinatorial Optimization and Applications. COCOA 2013. Lecture Notes in Computer Science, vol 8287. Springer, Cham. https://doi.org/10.1007/978-3-319-03780-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-03780-6_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03779-0

  • Online ISBN: 978-3-319-03780-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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