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An Efficient Multi-objective Evolutionary Algorithm for a Practical Dynamic Pickup and Delivery Problem

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Intelligent Computing Theories and Application (ICIC 2022)

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Abstract

Recently, practical dynamic pickup and delivery problem (DPDP) has become a challenging problem in manufacturing enterprises, due to the uncertainties of customers’ requirements and production processes. This paper proposes a multi-objective evolutionary algorithm based on decomposition with four efficient local search strategies, called MOEA/D-ES, which can well solve a practical DPDP with constraints like dock, time windows, capacity and last-in-first-out loading. This method decomposes the problem under consideration into many subproblems. The experimental results on 40 real-world logistics problem instances, offered by Huawei in the competition at ICAPS 2021, validate the high efficiency and effectiveness of our proposed method.

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Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 510860, China

    Junchuang Cai, Qingling Zhu, Qiuzhen Lin, Jianqiang Li, Jianyong Chen & Zhong Ming

Authors
  1. Junchuang Cai
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  2. Qingling Zhu
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  3. Qiuzhen Lin
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  4. Jianqiang Li
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  5. Jianyong Chen
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  6. Zhong Ming
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Corresponding author

Correspondence to Zhong Ming .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

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

    Kang-Hyun Jo

  3. Xi'an Polytechnic University, Xi'an, China

    Junfeng Jing

  4. The University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

  5. Polytecnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  6. Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Cai, J., Zhu, Q., Lin, Q., Li, J., Chen, J., Ming, Z. (2022). An Efficient Multi-objective Evolutionary Algorithm for a Practical Dynamic Pickup and Delivery Problem. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2022. Lecture Notes in Computer Science, vol 13393. Springer, Cham. https://doi.org/10.1007/978-3-031-13870-6_3

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  • DOI: https://doi.org/10.1007/978-3-031-13870-6_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13869-0

  • Online ISBN: 978-3-031-13870-6

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