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Research on EVRP of Cold Chain Logistics Distribution Based on Improved Ant Colony Algorithm

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Artificial Intelligence and Security (ICAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13338))

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Abstract

The distribution of fresh products is an urgent problem to be solved. In this paper, on the basis of considering the problem of vehicle path planning in the logistics distribution process, the distribution of fresh products by electric refrigerated vehicles is added. Considering that the electricity of refrigerated trucks will be consumed by low-temperature restrictions in addition to being used for vehicle driving, the vehicle routing problem of electric refrigerated trucks is constructed with the goal of minimizing the total cost of fixed costs, power consumption costs, cargo damage costs, and penalty costs. And by improving the transition probability and pheromone update of the traditional ant colony algorithm, an improved ant colony algorithm is proposed to solve the model. Through the analysis of the improved ant colony algorithm and the traditional ant colony algorithm to solve the model, it can be seen that the improved ant colony algorithm proposed in this paper is effective and superior in solving the path planning problem of electric refrigerated vehicles.

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Author information

Authors and Affiliations

  1. College of Economics and Management, Shanghai Ocean University, Shanghai, 201306, China

    Jiye Cui & Daqing Wu

  2. Economic and Technological Development Zone, Nanchang Institute of Technology, 901 Yingxiong Dadao, Nanchang, 330044, China

    Daqing Wu

  3. Department of Mathematics, Faculty of Science, New Valley University, El-Karaga, 72511, Egypt

    Romany Fouad Mansour

Authors
  1. Jiye Cui
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  2. Daqing Wu
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  3. Romany Fouad Mansour
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Corresponding author

Correspondence to Daqing Wu .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Cui, J., Wu, D., Mansour, R.F. (2022). Research on EVRP of Cold Chain Logistics Distribution Based on Improved Ant Colony Algorithm. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13338. Springer, Cham. https://doi.org/10.1007/978-3-031-06794-5_43

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  • DOI: https://doi.org/10.1007/978-3-031-06794-5_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06793-8

  • Online ISBN: 978-3-031-06794-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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