Skip to main content

Advertisement

Log in

Optimization of urban logistics terminal distribution based on cellular automaton model

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

In this paper, a method of urban terminal network location based on cellular automaton and genetic algorithm is proposed for the lack of scientific and standardized evaluation system in urban terminal network location problem. In this method, on the basis of considering the influencing factors, location principles and location steps of network location, the location model of urban terminal based on cellular automaton is established. To evaluate layout of urban logistics terminal, an evaluation index of competitiveness is built up. Then, calculation method based on logic of the genetic algorithm is used to solve the optimization result of layout through the comparison of the evaluation index. Finally, the effectiveness of the proposed method is illustrated through the simulation based on the actual data from an express company.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig.3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Awasthi A, Chauhan S, Goyal SK (2011) A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Math Comput Model 53(2):98–109

    Article  MathSciNet  Google Scholar 

  2. Silva FJ, de la Figuera DS (2007) A capacitated facility location problem with constrained backlogging probabilities. Int J Prod Res 45(21):5117–5134

    Article  Google Scholar 

  3. Zhuge D, Shucheng Yu, Zhen Lu et al (2016) Multi-period distribution center l-ocation and scale decision in supply chain network. Comput Ind Eng 101:216–226

    Article  Google Scholar 

  4. Chen YC (2002) An application of fuzzy set theory to the external performance evaluation of distribution centers in logistics. Soft Comput 6(1):64–70

    Article  Google Scholar 

  5. Georgiadis MC, Tsiakis P, Longinidis P, Sofioglou MK (2011) Optimal design of supply chain networks under uncertain transient demand variations. Omega 39:254–272

    Article  Google Scholar 

  6. Sadjady H, Davoudpour H (2012) Two-echelon, multi-commodity supply chain network design with mode selection, lead-times and inventory costs. Comput Oper Res 39:1345–1354

    Article  MathSciNet  Google Scholar 

  7. He J, Huang Y, Chang D (2015) Simulation-based heuristic method for container supply chain network optimization. Adv Eng Inform 29:339–354

    Article  Google Scholar 

  8. Yolmeh A, Salehi N (2015) An outer approximation method for an integration of supply chain network designing and assembly line balancing under uncertainty. Comput Ind Eng 83:297–306

    Article  Google Scholar 

  9. Asian S, Nie X (2014) Coordination in supply chains with uncertain demand and disruption risks: existence, analysis, and insights. IEEE Trans Syst Man Cybern Syst 44:1139–1154

    Article  Google Scholar 

  10. Zhuge D, Shucheng Yu, Zhen Lu, Wang W (2016) Multi-period distribution center location and scale decision in supply chain network. Comput Ind Eng 101:216–226

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by “National Natural Science Foundation of China (Grant No. 71461026)”, and “13th Five Year Plan of Jilin Provincial Department of Education (2018)”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chengyou Cui.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cui, C., Xu, Q. Optimization of urban logistics terminal distribution based on cellular automaton model. Artif Life Robotics 27, 142–148 (2022). https://doi.org/10.1007/s10015-021-00722-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-021-00722-x

Keywords

Navigation