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Speed optimizations for liner networks with business constraints

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  • Reinhardt, Line Blander
  • Pisinger, David
  • Sigurd, Mikkel M.
  • Ahmt, Jonas

Abstract

In 2018 the International Maritime Organization (IMO) agreed to cut the shipping sector’s overall CO2 output by 50% by 2050. One of the key methods in reaching this goal is to improve operations to limit fuel consumption. However, it is difficult to optimize speed for a complete liner shipping network as routes interact with each other, and several business constraints must be respected. This paper presents a unified model for speed optimization of a liner shipping network, satisfying numerous real-life business constraints. The speed optimization is in this research achieved by rescheduling the port call times of a network, thus, the network is not changed. The business constraints are among others related to transit times, port work shifts and emission control areas. Other restrictions are fixed times for canal crossing, speed restrictions in the piracy areas and desire for robust solutions. Vessel sharing agreements and other collaboration between companies must also be included. The modeling of the different restrictions is described in detail and tested on real-life data. The scientific contribution of this paper is threefold: We present a unified model for speed optimization together with numerous business constraints. We present a general framework for handling routes with different frequencies. Moreover, we present a bi-objective model for balancing robustness of schedules against fuel consumption. The tests show that the real-life requirements can be handled by mixed integer programming and that the model finds significant reductions of bunker consumption and cost for large-scale real-life instances.

Suggested Citation

  • Reinhardt, Line Blander & Pisinger, David & Sigurd, Mikkel M. & Ahmt, Jonas, 2020. "Speed optimizations for liner networks with business constraints," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1127-1140.
    • Handle: RePEc:eee:ejores:v:285:y:2020:i:3:p:1127-1140
    DOI: 10.1016/j.ejor.2020.02.043
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    Cited by:

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    2. Asghari, Mohammad & Jaber, Mohamad Y. & Mirzapour Al-e-hashem, S.M.J., 2023. "Coordinating vessel recovery actions: Analysis of disruption management in a liner shipping service," European Journal of Operational Research, Elsevier, vol. 307(2), pages 627-644.
    3. Liqian Yang & Gang Chen & Jinlou Zhao & Niels Gorm Malý Rytter, 2020. "Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping," Sustainability, MDPI, vol. 12(9), pages 1-24, May.
    4. Kazemi, Ahmad & Ernst, Andreas T. & Krishnamoorthy, Mohan & Le Bodic, Pierre, 2021. "Locomotive fuel management with inline refueling," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1077-1096.
    5. 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).
    6. 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).
    7. Wang, Yadong & Wang, Shuaian, 2021. "Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    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.

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