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Hyper-heuristic Three-Dimensional Estimation of Distribution Algorithm for Distributed Assembly Permutation Flowshop Scheduling Problem

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Advanced Intelligent Computing Technology and Applications (ICIC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14086))

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Abstract

For the distributed assembly permutation flowshop scheduling problem (DAPFSP) to minimize the maximum completion time, this study suggests a hyper-heuristic three-dimensional estimation of distribution algorithm (HH3DEDA) for solving it. The HH3DEDA consists of a high-level strategy (HLS) domain and a low-level problem (LLP) domain. The HLS domain guides the global search direction of the algorithm, while the LLP domain is responsible for searching local information in the problem domain. The HH3DEDA in this paper uses a variety of optimization strategies and metaheuristics that allow for global search and optimization, with the simultaneous setting up of nine variable neighborhood local search operations, and the arrangement of them as HLS domain individuals. Concurrently, the three-dimensional distribution estimation algorithm (3DEDA) is used in the HLS domain to learn the block structure of high-quality individuals in the HLS domain and their location information., and generating new HLS domain individuals by sampling the probability model in 3DEDA, then a series of ordered heuristic operators represented by each new individual generated at the HLS domain is used as a new heuristic algorithm at the LLP domain to perform a more in-deep neighborhood search in the problem domain.

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Acknowledgments

The authors are sincerely grateful to the anonymous reviewers for their insightful comments and suggestions, which greatly improve this paper. This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 72201115, 62173169, and 61963022), the Yunnan Fundamental Research Projects (Grant No. 202201BE070001050 and 202301AU070069), and the Basic Research Key Project of Yunnan Province (Grant No. 202201AS070030).

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Authors and Affiliations

  1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China

    Xiao Li, Zi-Qi Zhang, Rong Hu, Bin Qian & Kun Li

  2. School of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, 650500, China

    Rong Hu

Authors
  1. Xiao Li
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  2. Zi-Qi Zhang
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  3. Rong Hu
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  4. Bin Qian
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  5. Kun Li
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Corresponding author

Correspondence to Zi-Qi Zhang .

Editor information

Editors and Affiliations

  1. Eastern Institute of Technology, Zhejiang, China

    De-Shuang Huang

  2. University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

  3. Zhengzhou University of Light Industry, Zhengzhou, China

    Baohua Jin

  4. Zhong Yuan University of Technology, Zhengzhou, China

    Boyang Qu

  5. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  6. Department of Computer Science, Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Li, X., Zhang, ZQ., Hu, R., Qian, B., Li, K. (2023). Hyper-heuristic Three-Dimensional Estimation of Distribution Algorithm for Distributed Assembly Permutation Flowshop Scheduling Problem. In: Huang, DS., Premaratne, P., Jin, B., Qu, B., Jo, KH., Hussain, A. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2023. Lecture Notes in Computer Science, vol 14086. Springer, Singapore. https://doi.org/10.1007/978-981-99-4755-3_34

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  • DOI: https://doi.org/10.1007/978-981-99-4755-3_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-4754-6

  • Online ISBN: 978-981-99-4755-3

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