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Liner shipping service scheduling and cargo allocation

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  • Koza, David Franz

Abstract

Tactical service scheduling and operational cargo allocation are two interdependent problems in liner shipping. The schedules and sailing speeds of individual liner shipping services and the synchronization among all services determine the transit times of containers through a liner shipping network. On the other hand, the market demand in terms of container volume and expected transit times between origin and destination ports drive the schedule design of liner shipping services. We present a graph-based model and a branch-and-price algorithm to solve the combined problem. The goal is to minimize the difference between fuel consumption costs and revenues from transporting containers under consideration of transit time limits. Fuel consumption is modeled as a function of both speed and payload. Results are presented for 12 liner shipping networks and emphasize the importance of explicitly modeling schedules in large networks; transshipment times and thus transit times may be severely miscalculated otherwise. The results further show that neglecting payload in the fuel consumption function can result in suboptimal service schedules and cargo routing decisions.

Suggested Citation

  • Koza, David Franz, 2019. "Liner shipping service scheduling and cargo allocation," European Journal of Operational Research, Elsevier, vol. 275(3), pages 897-915.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:3:p:897-915
    DOI: 10.1016/j.ejor.2018.12.011
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    Cited by:

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    3. Yuzhe Zhao & Yujun Fan & Jingmiao Zhou & Haibo Kuang, 2019. "Bi-Objective Optimization of Vessel Speed and Route for Sustainable Coastal Shipping under the Regulations of Emission Control Areas," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    4. Dan Zhuge & Shuaian Wang & Lu Zhen & Gilbert Laporte, 2021. "Subsidy design in a vessel speed reduction incentive program under government policies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(3), pages 344-358, April.
    5. Trivella, Alessio & Corman, Francesco & Koza, David F. & Pisinger, David, 2021. "The multi-commodity network flow problem with soft transit time constraints: Application to liner shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    6. Hellsten, Erik Orm & Sacramento, David & Pisinger, David, 2022. "A branch-and-price algorithm for solving the single-hub feeder network design problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 902-916.
    7. Ming Liu & Rongfan Liu & E Zhang & Chengbin Chu, 0. "Eco-friendly container transshipment route scheduling problem with repacking operations," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
    8. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    9. 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.
    10. Hu, Shu & Yu, Dennis Z. & Fu, Ke, 2023. "Online platforms’ warehouse capacity allocation strategies for multiple products," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

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