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Task Set Scheduling of Airport Freight Station Based on Parallel Artificial Bee Colony Algorithm

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1159))

Abstract

In order to improve the operation efficiency in airport freight station, the task scheduling problem of freight station is studied in this paper. Based on the mathematical model of the whole system, the integer encoding and continuous encoding methods are proposed to describe the sequence of tasks, then the parallel artificial bee colony algorithm is used to optimize the tasks set. The simulation results show that proposed improved artificial bee colony algorithm based on the two encoding methods are effective, and compared with the traditional bee colony algorithm, the parallel algorithm can reduce the optimization time and improve the optimization efficiency without affecting the optimization results.

Supported by organization Program of Educational Committee of Henan Province (18A120005), Science & Technology Program of Henan Province (172102210588), and Science and Technology Key Project of Henan Province (162102410056).

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Acknowledgement

The authors acknowledge the support of Program of Educational Committee of Henan Province (18A120005), Science & Technology Program of Henan Province (172102210588), and Science and Technology Key Project of Henan Province (162102410056).

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Authors and Affiliations

  1. Zhongyuan Petersburg Aviation College, Zhongyuan University of Technology, 41 Zhongyuan Road, Zhengzhou, 450007, China

    Haiquan Wang & Zhe Dong

  2. School of Electric and Information Engineering, Zhongyuan University of Technology, 41 Zhongyuan Road, Zhengzhou, 450007, China

    Jianhua Wei, Menghao Su, Zhe Dong & Shanshan Zhang

Authors
  1. Haiquan Wang
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  2. Jianhua Wei
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  3. Menghao Su
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  4. Zhe Dong
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  5. Shanshan Zhang
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Corresponding author

Correspondence to Haiquan Wang .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Wang, H., Wei, J., Su, M., Dong, Z., Zhang, S. (2020). Task Set Scheduling of Airport Freight Station Based on Parallel Artificial Bee Colony Algorithm. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_37

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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