IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i23p3797-d1533963.html
   My bibliography  Save this article

Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain

Author

Listed:
  • Zhichao Hong

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China)

  • Hao Shen

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China)

  • Wenjie Sun

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China)

  • Jin Zhang

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
    National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
    National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 610031, China)

  • Hongbin Liang

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
    National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
    National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 610031, China)

  • Gang Zhao

    (China Railway Union International Container Smart Logistics Chengdu Co., Ltd., Chengdu 610084, China)

Abstract

The purpose of this study is to solve the problem of low load factor and profit margin in the point-to-point transportation of international freight trains through the assembly transportation organization mode. A bi-objective location-routing optimization model is constructed to optimize problems, such as the location of the assembly center, route of freight assembly, frequency of international freight trains, and number of formations. The objectives are to minimize the total comprehensive cost and maximize the average satisfaction of the shippers. Considering the impact of blockchain technology, the proportion of customs clearance time reduction after blockchain implementation, the proportion of customs clearance fee reduction after blockchain implementation, and the cost of blockchain technology are introduced into the model. The case study is based on railroad transportation data for 2022. In this case, 43 stations in the Indo-China Peninsula are selected as origin stations, and two Chinese stations are designated terminal stations. An improved NSGA-II algorithm (ANSGAII-OD) is proposed to resolve the location-routing optimization model. This algorithm is based on opposition-based learning and its dominant strength. The case study indicates that assembly transportation is advantageous compared with direct transportation. Moreover, the comprehensive cost is reduced by 19.77%. Furthermore, blockchain technology can effectively reduce costs and improve transportation efficiency. After the implementation of blockchain technology, the comprehensive cost is reduced by 8.10%, whereas the average satisfaction of shippers is increased by 10.35%.

Suggested Citation

  • Zhichao Hong & Hao Shen & Wenjie Sun & Jin Zhang & Hongbin Liang & Gang Zhao, 2024. "Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain," Mathematics, MDPI, vol. 12(23), pages 1-23, November.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3797-:d:1533963
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/23/3797/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/23/3797/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fosso Wamba, Samuel & Queiroz, Maciel M. & Trinchera, Laura, 2020. "Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Yang, Chung-Shan, 2019. "Maritime shipping digitalization: Blockchain-based technology applications, future improvements, and intention to use," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 108-117.
    3. Zhao, Laijun & Zhao, Yue & Hu, Qingmi & Li, Huiyong & Stoeter, Johan, 2018. "Evaluation of consolidation center cargo capacity and loctions for China railway express," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 117(C), pages 58-81.
    4. Zhou, Yong-Wu & Li, Jicai & Zhong, Yuanguang, 2018. "Cooperative advertising and ordering policies in a two-echelon supply chain with risk-averse agents," Omega, Elsevier, vol. 75(C), pages 97-117.
    5. Yu Zhang & Nan Liu, 2023. "Blockchain adoption in serial logistics service chain: value and challenge," International Journal of Production Research, Taylor & Francis Journals, vol. 61(13), pages 4374-4401, July.
    6. Olli-Pekka Hilmola & Weidong Li & Yulia Panova, 2021. "Development Status and Future Trends for Eurasian Container Land Bridge Transport," Logistics, MDPI, vol. 5(1), pages 1-12, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jie Zhang & Chen Ruan, 2024. "Blockchain Technology and Corporate Performance: Empirical Evidence from Listed Companies in China," Sustainability, MDPI, vol. 16(21), pages 1-18, October.
    2. Ahmed Antwi-Boampong & David King Boison & Musah Osumanu Doumbia & Afia Nyarko Boakye & Linda Osei-Fosua & Kwame Owiredu Sarbeng, 2022. "Factors Affecting Port Users’ Behavioral Intentions to Adopt Financial Technology (Fintech) in Ports in Sub-Saharan Africa: A Case of Ports in Ghana," FinTech, MDPI, vol. 1(4), pages 1-14, November.
    3. Simon Wong & John Kun Woon Yeung & Yui-Yip Lau & Tomoya Kawasaki & Raymond Kwong, 2024. "A Critical Literature Review on Blockchain Technology Adoption in Supply Chains," Sustainability, MDPI, vol. 16(12), pages 1-40, June.
    4. Choi, Tsan-Ming & Siqin, Tana, 2022. "Blockchain in logistics and production from Blockchain 1.0 to Blockchain 5.0: An intra-inter-organizational framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    5. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    6. Jia Liu & Cuixia Li, 2023. "Dynamic Game Analysis on Cooperative Advertising Strategy in a Manufacturer-Led Supply Chain with Risk Aversion," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    7. Liu Jiaguo & Zhang Huimin & Zhao Huida, 2021. "Blockchain Technology Investment and Sharing Strategy of Port Supply Chain Under Competitive Environment," Journal of Systems Science and Information, De Gruyter, vol. 9(3), pages 280-309, June.
    8. Mahmoona Khalil & Kausar Fiaz Khawaja & Muddassar Sarfraz, 2022. "The adoption of blockchain technology in the financial sector during the era of fourth industrial revolution: a moderated mediated model," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2435-2452, August.
    9. Jinxuan Song & Xu Yan, 2023. "Impact of Government Subsidies, Competition, and Blockchain on Green Supply Chain Decisions," Sustainability, MDPI, vol. 15(4), pages 1-27, February.
    10. Olli-Pekka Hilmola & Weidong Li, 2023. "Drivers of railway container transports between China and Finland," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-19, December.
    11. Dehghani, Milad & William Kennedy, Ryan & Mashatan, Atefeh & Rese, Alexandra & Karavidas, Dionysios, 2022. "High interest, low adoption. A mixed-method investigation into the factors influencing organisational adoption of blockchain technology," Journal of Business Research, Elsevier, vol. 149(C), pages 393-411.
    12. Fosso Wamba, Samuel & Queiroz, Maciel M. & Trinchera, Laura, 2024. "The role of artificial intelligence-enabled dynamic capability on environmental performance: The mediation effect of a data-driven culture in France and the USA," International Journal of Production Economics, Elsevier, vol. 268(C).
    13. Fink, Alexander A. & Klöckner, Maximilian & Räder, Tobias & Wagner, Stephan M., 2022. "Supply chain management accelerators: Types, objectives, and key design features," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    14. Kirti Nayal & Rakesh D. Raut & Balkrishna E. Narkhede & Pragati Priyadarshinee & Gajanan B. Panchal & Vidyadhar V. Gedam, 2023. "Antecedents for blockchain technology-enabled sustainable agriculture supply chain," Annals of Operations Research, Springer, vol. 327(1), pages 293-337, August.
    15. Pattanayak, Sirsha & Ramkumar, M. & Goswami, Mohit & Rana, Nripendra P., 2024. "Blockchain technology and supply chain performance: The role of trust and relational capabilities," International Journal of Production Economics, Elsevier, vol. 271(C).
    16. He, Yi & Wang, Hang & Guo, Qiang & Xu, Qingyun, 2019. "Coordination through cooperative advertising in a two-period consumer electronics supply chain," Journal of Retailing and Consumer Services, Elsevier, vol. 50(C), pages 179-188.
    17. Suneet Singh & Ashish Dwivedi & Saurabh Pratap, 2023. "Sustainable Maritime Freight Transportation: Current Status and Future Directions," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    18. Wang, Zhenjie & Zhang, Dezhi & Tavasszy, Lóránt & Fazi, Stefano, 2023. "Integrated multimodal freight service network design and pricing with a competing service integrator and heterogeneous shipper classes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    19. Yongming Wang & Umar Iqbal & Yingmei Gong, 2021. "The Performance of Resilient Supply Chain Sustainability in Covid-19 by Sourcing Technological Integration," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    20. Chang, Jasmine (Aichih) & Katehakis, Michael N. & Shi, Jim (Junmin) & Yan, Zhipeng, 2021. "Blockchain-empowered Newsvendor optimization," International Journal of Production Economics, Elsevier, vol. 238(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3797-:d:1533963. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.