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Balanced Truck Dispatching Strategy for Inter-Terminal Container Transportation with Demand Outsourcing

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Listed:
  • Yucheng Zhao

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao An Highway, Shanghai 201804, China)

  • Yuxiong Ji

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao An Highway, Shanghai 201804, China)

  • Yujing Zheng

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao An Highway, Shanghai 201804, China)

Abstract

This study proposes a balanced truck dispatching strategy for inter-terminal transportation (ITT) in large ports, incorporating proactive demand outsourcing to address stochastic and imbalanced ITT demand. A portion of ITT tasks are intentionally outsourced to third-party public trucks at a higher cost, so that self-owned trucks can be reserved for more critical tasks. The ITT system is modeled as a closed Jackson network, in which self-owned trucks circulate among terminals and routes. An optimization model is developed to determine the optimal proactive outsourcing ratios for origin–destination terminal pairs and the appropriate fleet size of self-owned trucks, aiming to minimize total transportation costs. Reactive outsourcing is also included to handle occasional truck shortages. A mean value analysis method is used to evaluate system performance with given decisions, and a differential evolution algorithm is employed for optimization. The case study of Shanghai Yangshan Port demonstrates that the proposed strategy reduces total system cost by 9.8% compared to reactive outsourcing. The results also highlight the importance of jointly optimizing outsourcing decisions and fleet size. This study provides theoretical insights and practical guidance for ITT system management under demand uncertainty.

Suggested Citation

  • Yucheng Zhao & Yuxiong Ji & Yujing Zheng, 2025. "Balanced Truck Dispatching Strategy for Inter-Terminal Container Transportation with Demand Outsourcing," Mathematics, MDPI, vol. 13(13), pages 1-15, July.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2163-:d:1693265
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    References listed on IDEAS

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    1. Heilig, Leonard & Lalla-Ruiz, Eduardo & Voß, Stefan, 2017. "Multi-objective inter-terminal truck routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 178-202.
    2. Qu Hu & Bart Wiegmans & Francesco Corman & Gabriel Lodewijks, 2019. "Integration of inter-terminal transport and hinterland rail transport," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 807-831, September.
    3. Leonard Heilig & Eduardo Lalla-Ruiz & Stefan Voß, 2017. "port-IO: an integrative mobile cloud platform for real-time inter-terminal truck routing optimization," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 504-534, December.
    4. Tierney, Kevin & Voß, Stefan & Stahlbock, Robert, 2014. "A mathematical model of inter-terminal transportation," European Journal of Operational Research, Elsevier, vol. 235(2), pages 448-460.
    5. Bharat Raj Wagle & R. P. Ghimire, 2024. "Performance Evaluations of Vehicle Sharing in Closed Queueing Networks System," SN Operations Research Forum, Springer, vol. 5(2), pages 1-16, June.
    6. Leonard Heilig & Stefan Voß, 2017. "Inter-terminal transportation: an annotated bibliography and research agenda," Flexible Services and Manufacturing Journal, Springer, vol. 29(1), pages 35-63, March.
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