Skip to main content
SpringerLink
Log in
Book cover

International Conference on Adaptive and Intelligent Systems

ICAIS 2022: Artificial Intelligence and Security pp 537–548Cite as

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

  • Conference paper
  • First Online:

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

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.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Feng, S.: Research on vehicle routing problem of fresh products with pure electric refrigerator truck. Comput. Eng. Appl. 055(009), 237–242 (2019)

    Google Scholar 

  2. Zhang, C., Li, Y.: Research on optimization decision of urban cold chain logistics distribution system from the perspective of low carbon. Ind. Eng. Manag., 1–17 (2021)

    Google Scholar 

  3. Zhao, L.: Electric vehicle route optimization for fresh logistics distribution based on time-varying traffic congestion. J. Transp. Syst. Eng. Inf. Technol. 20(5), 9 (2020)

    Google Scholar 

  4. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manag. Sci. 6(1), 80–91 (1959)

    Google Scholar 

  5. Desrochers, M., Solomon, D.M.: A new optimization algorithm for the vehicle routing problem with time windows. Oper. Res. 40(2), 342–354 (1992)

    Article  MathSciNet  Google Scholar 

  6. Brandao, J.: Iterated local search algorithm with ejection chains for the open vehicle routing problem with time windows. Comput. Ind. Eng. 120, 146–159 (2018)

    Google Scholar 

  7. Gan, Z.: Electric refrigerated vehicle routing optimization with time windows and energy consumption. Ind. Eng. Manag. 27(01), 204–210 (2022)

    Google Scholar 

  8. Li, L.: Route optimization of multi-vehicle cold chain logistics for fresh agricultural products. J. Chain Agric. Univ. 26(07), 115–123 (2021)

    Google Scholar 

  9. Ren, L.: Knowledge based ant colony algorithm for cold chain logistics distribution path optimization. Control Decis. 37(03), 545–554 (2022)

    Google Scholar 

  10. Li, J.: Multi-objective cold chain distribution optimization based on fuzzy time window. Comput. Eng. Appl. 57(23), 255–262 (2021)

    Google Scholar 

  11. Bac, U., Erdem, M.: Optimization of electric vehicle recharge schedule and routing problem with time windows and partial recharge: A comparative study for an urban logistics fleet. Sustain. Cities Soc. 70, 102883 (2021)

    Article  Google Scholar 

  12. Kancharla, S.R., Ramadurai, G.: Electric vehicle routing problem with non-linear charging and load-dependent discharging. Expert Syst. Appl. 160, 113714 (2020)

    Google Scholar 

  13. Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperative agents. IEEE Trans. Syst. Man Cybern. 26(1), 29–41 (1996)

    Article  Google Scholar 

  14. Kallehauge, B.: Formulations and exact algorithms for the vehicle routing problem with time windows. Comput. Oper. Res. 35(7), 2307–2330 (2008)

    Article  MathSciNet  Google Scholar 

  15. Zhang, L.: Research on dynamic distribution vehicle route optimization under the influence of carbon emission. Chin. J. Manag. Sci., 1–13 (2021). https://doi.org/10.16381/j.cnki.issn1003-207x.2019.0816

Download references

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
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daqing Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Romany Fouad Mansour
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

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

Download citation

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

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06793-8

  • Online ISBN: 978-3-031-06794-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation