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Multimodal Transportation Route Optimization of Emergency Supplies Under Uncertain Conditions

Author

Listed:
  • Zhongyan Xu

    (College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China)

  • Changjiang Zheng

    (College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China)

  • Shukang Zheng

    (College of Environment, Hohai University, Nanjing 210098, China)

  • Genghua Ma

    (Coastal and Offshore Engineering, College of Harbour, Hohai University, Nanjing 210098, China)

  • Zhichao Chen

    (College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China)

Abstract

In recent years, the frequency of sudden disaster events has increased significantly, leading to substantial and often irreparable losses for society and individuals. Although the comprehensive development of China’s transportation network has laid a solid foundation for the transportation of emergency supplies, the construction of an optimized transportation system for emergency logistics still faces considerable challenges, particularly given the uncertainties of the transportation environment. To ensure the efficient delivery of emergency supplies to disaster sites via optimal routes and the utilization of multimodal transport for logistics distribution, this paper addresses the following key objectives. First, recognizing the uncertainties in parameters such as transportation time and cost due to dynamic changes in the transportation environment as well as the limitations of transshipment capacity, we developed a multimodal transport path optimization model for emergency supplies. The model aims to minimize both transportation time and costs. Second, in addressing uncertain parameters, we employed the theory of interval number ranking, defining a risk coefficient to convert uncertain parameters into deterministic ones. This enabled a deterministic transformation of the model. Additionally, a weighted scoring method was applied to assign weights to each objective, effectively transforming the multi-objective optimization problem into a single-objective problem. Finally, we applied the genetic algorithm, particle swarm optimization algorithm, and a hybrid genetic–particle swarm algorithm to solve the model. The effectiveness of the model and the superiority of the hybrid algorithm were verified through case studies. Furthermore, a sensitivity analysis of the parameters and an investigation into the influence of the risk coefficient were conducted, providing valuable insights for relevant decision-making departments in formulating emergency material transportation plans.

Suggested Citation

  • Zhongyan Xu & Changjiang Zheng & Shukang Zheng & Genghua Ma & Zhichao Chen, 2024. "Multimodal Transportation Route Optimization of Emergency Supplies Under Uncertain Conditions," Sustainability, MDPI, vol. 16(24), pages 1-26, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:10905-:d:1542455
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    References listed on IDEAS

    as
    1. Ghane-Ezabadi, Mohammad & Vergara, Hector A., 2016. "Decomposition approach for integrated intermodal logistics network design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 53-69.
    2. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    3. Hongbin Liu & Guopeng Song & Tianyu Liu & Bo Guo, 2022. "Multitask Emergency Logistics Planning under Multimodal Transportation," Mathematics, MDPI, vol. 10(19), pages 1-25, October.
    4. Lin Li & Qiangwei Zhang & Tie Zhang & Yanbiao Zou & Xing Zhao, 2023. "Optimum Route and Transport Mode Selection of Multimodal Transport with Time Window under Uncertain Conditions," Mathematics, MDPI, vol. 11(14), pages 1-25, July.
    5. Dandan Chen & Yong Zhang & Liangpeng Gao & Russell G. Thompson, 2019. "Optimizing Multimodal Transportation Routes Considering Container Use," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    6. Ishfaq, Rafay & Sox, Charles R., 2012. "Design of intermodal logistics networks with hub delays," European Journal of Operational Research, Elsevier, vol. 220(3), pages 629-641.
    7. Jixiao Wu & Yinghui Wang, 2021. "Distribution of the Emergency Supplies in the COVID-19 Pandemic: A Cloud Computing Based Approach," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-18, October.
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