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Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I

Research Article

Location and Path Planning of Cross-Border E-Commerce Logistics Distribution Center in Cloud Computing Environment

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  • @INPROCEEDINGS{10.1007/978-3-030-67871-5_4,
        author={Yi-huo Jiang},
        title={Location and Path Planning of Cross-Border E-Commerce Logistics Distribution Center in Cloud Computing Environment},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2021},
        month={2},
        keywords={Cloud computing environment Cross-border E-commerce Logistics distribution Distribution center location Path planning},
        doi={10.1007/978-3-030-67871-5_4}
    }
    
  • Yi-huo Jiang
    Year: 2021
    Location and Path Planning of Cross-Border E-Commerce Logistics Distribution Center in Cloud Computing Environment
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-67871-5_4
Yi-huo Jiang1,*
  • 1: Fuzhou University of International Studies and Trade
*Contact email: hbgv96012@126.com

Abstract

In order to solve the problem of high transportation cost in the range of transportation distance from 3.5 km to 7.5 km, this paper proposes a method of location and path planning for cross-border e-commerce logistics distribution center in cloud computing environment. Cross-border e-commerce logistics distribution center location model is established under the cloud computing environment to achieve cross-border e-commerce logistics distribution center location. Cross-border e-commerce logistics path planning is realized by constructing cross-border e-commerce logistics path planning model in cloud computing environment. The logistic path planning model of cross-border e-commerce includes time and event sequence sub-model, state variable quantum model, external information sub-model, state transfer sub-model, objective function and optimal strategy sub-model. In order to prove that the transportation cost of this method is lower in the range of 3.5 km to 7.5 km, two original methods are compared with this method. The experimental results show that the transportation cost of this method is much lower than that of the other two methods, and the cost is reduced successfully.

Keywords
Cloud computing environment, Cross-border E-commerce, Logistics distribution, Distribution center location, Path planning
Published
2021-02-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67871-5_4
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