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Research on Optimization and Design of Sustainable Urban Underground Logistics Network Framework

Author

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  • Hairui Wei

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

  • Anlin Li

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

  • Nana Jia

    (Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China)

Abstract

As a new mode of transportation, the underground logistics system (ULS) has become one of the solutions to the problems of environmental pollution and traffic congestion. Considering the environmental and economic factors in urban logistics, this paper conducts comprehensive design and optimization research on the network nodes and passages of urban underground logistics and proposes a relatively complete framework for a sustainable underground logistics network. A hybrid method is proposed, which includes the set cover model used to perform the first location of urban underground logistics nodes, the fuzzy clustering method applied to classify the located logistics nodes into the first-level and second-level nodes considering the congestion in different urban areas of the city and a mixed integer programming model proposed to optimize and design the underground logistics passage to find optimal passage parameters at every underground logistics node. Based on the above hybrid method, a sustainable underground logistics network framework including all-levels logistics nodes and passages is formed, with a subdistrict of Nanjing as a case study. The discussion of results shows that this underground logistics network framework proposal is very effective in reducing logistics time cost, exhaust emission and congestion cost. It provides support for decisions in the design and development of urban sustainable underground logistics networks.

Suggested Citation

  • Hairui Wei & Anlin Li & Nana Jia, 2020. "Research on Optimization and Design of Sustainable Urban Underground Logistics Network Framework," Sustainability, MDPI, vol. 12(21), pages 1-22, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9147-:d:439518
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Seok Jin Youn & Yong-Jae Lee & Ha-Eun Han & Chang-Woo Lee & Donggyun Sohn & Chulung Lee, 2024. "A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems," Sustainability, MDPI, vol. 16(15), pages 1-32, August.
    2. Han Zhang & Yongbo Lv & Jianwei Guo, 2022. "New Development Direction of Underground Logistics from the Perspective of Public Transport: A Systematic Review Based on Scientometrics," Sustainability, MDPI, vol. 14(6), pages 1-31, March.
    3. Xu Zhang & Fei-Yu Jin & Xu-Mei Yuan & Hai-Yan Zhang, 2021. "Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time," Sustainability, MDPI, vol. 13(15), pages 1-18, July.
    4. Filip Škultéty & Dominika Beňová & Jozef Gnap, 2021. "City Logistics as an Imperative Smart City Mechanism: Scrutiny of Clustered EU27 Capitals," Sustainability, MDPI, vol. 13(7), pages 1-16, March.
    5. Jiaojiao Li & Jianjun Dong & Rui Ren & Zhilong Chen, 2024. "Modeling Resilience of Metro-Based Urban Underground Logistics System Based on Multi-Layer Interdependent Network," Sustainability, MDPI, vol. 16(22), pages 1-23, November.
    6. Doğukan Toktaş & M. Ali Ülkü & Muhammad Ahsanul Habib, 2024. "Toward Greener Supply Chains by Decarbonizing City Logistics: A Systematic Literature Review and Research Pathways," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
    7. Nestor Shpak & Zoriana Dvulit & Liana Maznyk & WÅ‚odzimierz Sroka & Olha Podra & Nataliia Petryshyn, 2022. "An innovative approach to support interests' alignment in the context of transport management using semantic differential," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 18(3), pages 107-134.
    8. Di, Zhen & Yang, Lixing & Shi, Jungang & Zhou, Housheng & Yang, Kai & Gao, Ziyou, 2022. "Joint optimization of carriage arrangement and flow control in a metro-based underground logistics system," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 1-23.

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