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Simultaneous Optimization of Container Ship Sailing Speed and Container Routing with Transit Time Restrictions

Author

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  • Christian Va Karsten

    (DTU Management Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

  • Stefan Ropke

    (DTU Management Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

  • David Pisinger

    (DTU Management Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

Abstract

We introduce a decision support tool for liner shipping companies to optimally determine the sailing speed and needed fleet for a global network. We incorporate cargo routing decisions with tight transit time restrictions on each container such that we get a realistic picture of the utilization of the network. Furthermore, we show that it is possible to extend the model to include optimal time scheduling decisions such that the time associated with transshipments is also reflected accurately. To solve the speed optimization problem, we propose an exact algorithm based on Benders decomposition and column generation that exploits the separability of the problem. Computational results show that the method is applicable to liner shipping networks of realistic size and that it is important to incorporate cargo routing decisions when optimizing speed.

Suggested Citation

  • Christian Va Karsten & Stefan Ropke & David Pisinger, 2018. "Simultaneous Optimization of Container Ship Sailing Speed and Container Routing with Transit Time Restrictions," Transportation Science, INFORMS, vol. 52(4), pages 769-787, August.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:4:p:769-787
    DOI: 10.1287/trsc.2018.0818
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    References listed on IDEAS

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    Cited by:

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    2. Koza, David Franz, 2019. "Liner shipping service scheduling and cargo allocation," European Journal of Operational Research, Elsevier, vol. 275(3), pages 897-915.
    3. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong, 2023. "A branch-and-price heuristic algorithm for the bunkering operation problem of a liquefied natural gas bunkering station in the inland waterways," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 145-170.
    4. Qi, Yingxiu & Harrod, Steven & Psaraftis, Harilaos N. & Lang, Maoxiang, 2022. "Transport service selection and routing with carbon emissions and inventory costs consideration in the context of the Belt and Road Initiative," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    5. Sun, Xuting & Chung, Sai-Ho & Choi, Tsan-Ming & Sheu, Jiuh-Biing & Ma, Hoi Lam, 2020. "Combating lead-time uncertainty in global supply chain's shipment-assignment: Is it wise to be risk-averse?," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 406-434.
    6. Alba Martínez-López & Manuel Chica, 2020. "Joint Optimization of Routes and Container Fleets to Design Sustainable Intermodal Chains in Chile," Sustainability, MDPI, vol. 12(6), pages 1-23, March.
    7. Xiangang Lan & Xiaode Zuo & Qin Tao, 2023. "Container Shipping Optimization under Different Carbon Emission Policies: A Case Study," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    8. Zhuge, Dan & Wang, Shuaian & Wang, David Z.W., 2021. "A joint liner ship path, speed and deployment problem under emission reduction measures," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 155-173.
    9. Wang, Yadong & Gu, Yuyun & Wang, Tingsong & Zhang, Jun, 2022. "A risk-averse approach for joint contract selection and slot allocation in liner container shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    10. Wang, Yadong & Meng, Qiang & Jia, Peng, 2019. "Optimal port call adjustment for liner container shipping routes," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 107-128.

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