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Research on Hybrid Quantum Genetic Algorithm Based on Cross-Docking Delivery Vehicle Scheduling

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Cyber Security Intelligence and Analytics (CSIA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 928))

Abstract

Quantum genetic algorithm (QGA) is a new algorithm to solve the optimal problem by applying classical quantum theory to genetic algorithm and introducing quantum states into the traditional bit model. Cross-docking delivery vehicle scheduling is a classical combinatorial optimization problem. Based on QGA, in order to improve the speed and efficiency of logistics distribution process, this paper studies a hybrid QGA framework, proposes a new idea to solve the distribution optimization scheme in traditional logistics scheduling, and studies new strategies of quantum updating and probability adjustment, so as to make the method more suitable for the actual problems of logistics distribution.

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Acknowledgement

Fund Project: Research on Key Technologies of Intelligent Logistics System Based on Multi-Agent(SIT-i5201801).

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Authors and Affiliations

  1. Shenyang Institute of Technology, Fushun, 113122, Liaoning, China

    Yue Yang

Authors
  1. Yue Yang
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Corresponding author

Correspondence to Yue Yang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Zheng Xu

  2. University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. University of Guelph, Guelph, ON, Canada

    Ali Dehghantanha

  4. Kennesaw State University, Marietta, GA, USA

    Reza Parizi

  5. Manchester Metropolitan University, Stockport, UK

    Mohammad Hammoudeh

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Yang, Y. (2020). Research on Hybrid Quantum Genetic Algorithm Based on Cross-Docking Delivery Vehicle Scheduling. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_119

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