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A Best Possible Online Algorithm For Scheduling To Minimize Maximum Flow-Time On Bounded Batch Machines

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  • CHENGWEN JIAO

    (School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, People's Republic of China;
    School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China)

  • WENHUA LI

    (School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, People's Republic of China)

  • JINJIANG YUAN

    (School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, People's Republic of China)

Abstract

We consider online scheduling of unit length jobs on m identical parallel-batch machines. Jobs arrive over time. The objective is to minimize maximum flow-time, with the flow-time of a job being the difference of its completion time and its release time. A parallel-batch machine can handle up to b jobs simultaneously as a batch. Here, the batch capacity is bounded, that is b

Suggested Citation

  • Chengwen Jiao & Wenhua Li & Jinjiang Yuan, 2014. "A Best Possible Online Algorithm For Scheduling To Minimize Maximum Flow-Time On Bounded Batch Machines," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 31(04), pages 1-10.
  • Handle: RePEc:wsi:apjorx:v:31:y:2014:i:04:n:s0217595914500304
    DOI: 10.1142/S0217595914500304
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    Citations

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    Cited by:

    1. Lin, Ran & Wang, Jun-Qiang & Oulamara, Ammar, 2023. "Online scheduling on parallel-batch machines with periodic availability constraints and job delivery," Omega, Elsevier, vol. 116(C).
    2. Xing Chai & Wenhua Li & Yuejuan Zhu, 2021. "Online scheduling to minimize maximum weighted flow-time on a bounded parallel-batch machine," Annals of Operations Research, Springer, vol. 298(1), pages 79-93, March.
    3. Christoph Hertrich & Christian Weiß & Heiner Ackermann & Sandy Heydrich & Sven O. Krumke, 2022. "Online algorithms to schedule a proportionate flexible flow shop of batching machines," Journal of Scheduling, Springer, vol. 25(6), pages 643-657, December.

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