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Intelligent Scheduling of Distributed Displacement Pipeline Based on Hybrid Discrete Drosophila Optimization Algorithm

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Multimedia Technology and Enhanced Learning (ICMTEL 2021)

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In order to solve the problem of long scheduling time and low efficiency of interval number representation scheduling method, a distributed replacement Pipeline Intelligent Scheduling Based on hybrid discrete Drosophila optimization algorithm is proposed. According to the distributed permutation pipeline scheduling problem, the coding method based on operation is adopted to make the algorithm suitable for solving the scheduling problem. The hybrid discrete Drosophila optimization algorithm is used to solve the batch pipeline scheduling problem with the maximum completion time as the goal. In order to balance the local search ability of the algorithm, the evolutionary mechanism is combined with cooperative learning among groups. Build a mathematical model to achieve efficient scheduling in the maximum completion time. The simulation results show that the scheduling time of this method is short, and the overall scheduling efficiency is higher than 80%, which has good scheduling effect.

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Authors and Affiliations

  1. School of Information and Intelligence Engineering, University of Sanya, Sanya, 572022, HaiNan, China

    Pan Yuxia & Xie Guang

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  1. Pan Yuxia
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  2. Xie Guang
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Correspondence to Pan Yuxia .

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Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Weina Fu

  2. University of Jinan, Jinan, China

    Yuan Xu

  3. University of Leicester, Leicester, UK

    Shui-Hua Wang

  4. University of Leicester, Leicester, UK

    Yudong Zhang

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Yuxia, P., Guang, X. (2021). Intelligent Scheduling of Distributed Displacement Pipeline Based on Hybrid Discrete Drosophila Optimization Algorithm. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-82562-1_7

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  • DOI: https://doi.org/10.1007/978-3-030-82562-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82561-4

  • Online ISBN: 978-3-030-82562-1

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