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Online Early Work Maximization on Three Hierarchical Machines with a Common Due Date

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Frontiers of Algorithmic Wisdom (IJTCS-FAW 2022)

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Abstract

In this paper, we consider the online early work problems on three hierarchical machines with a common due date. When there is one machine of hierarchy 1, we propose an optimal online algorithm with a competitive ratio of 1.302. When there are two machines of hierarchy 1, we give a lower bound 1.276, and propose an online algorithm with a competitive ratio of 1.302.

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Acknowledgement

The work is supported in part by the National Natural Science Foundation of China [No. 12071417].

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Authors and Affiliations

  1. School of Mathematics and Statistics, Yunnan University, Kunming, 650504, China

    Man Xiao & Weidong Li

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  1. Man Xiao
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  2. Weidong Li
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Corresponding author

Correspondence to Weidong Li .

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Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Minming Li

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Xiaoming Sun

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Xiao, M., Li, W. (2022). Online Early Work Maximization on Three Hierarchical Machines with a Common Due Date. In: Li, M., Sun, X. (eds) Frontiers of Algorithmic Wisdom. IJTCS-FAW 2022. Lecture Notes in Computer Science, vol 13461. Springer, Cham. https://doi.org/10.1007/978-3-031-20796-9_8

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  • DOI: https://doi.org/10.1007/978-3-031-20796-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20795-2

  • Online ISBN: 978-3-031-20796-9

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