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A Metaheuristic Algorithm for Ship Weather Routing

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  • Stéphane Grandcolas

    (Laboratoire d’Informatique et Systèmes Aix Marseille Univ., Université de Toulon, CNRS, LIS)

Abstract

In recent years ship weather routing has attracted a lot of interest, resulting of the significant increase of transport by sea. The primary objective is to limit the costs, but other parameters, such as time, safety or preservation of the environment, can also be considered. These aspects and the fact that the domains of the variables are continuous make the problem difficult to solve. We propose a metaheuristic algorithm called WRM (for Weather Routing Metaheuristic) that aims at finding routes of minimal cost within a given time period. The cost can be the fuel oil consumption, the amount of greenhouse gas emissions or any other measure. It depends on the weather conditions that are expected and on the speed of the vessel (i.e., the speed over the ground, or any parameter correlated with the speed, such as the power level of the engine), which can vary all along the route. Constraints forbidding or penalizing the navigation in specific conditions or in some given areas can be easily enforced. The method is simple and general. It converges progressively towards the most promising regions, generating new potential way points which are not derived from a predefined mesh. Simulating the fuel oil consumption of the vessel according to the expected wind and waves conditions, we have performed experimentations that show the efficiency of the approach.

Suggested Citation

  • Stéphane Grandcolas, 2022. "A Metaheuristic Algorithm for Ship Weather Routing," SN Operations Research Forum, Springer, vol. 3(3), pages 1-16, September.
    • Handle: RePEc:spr:snopef:v:3:y:2022:i:3:d:10.1007_s43069-022-00140-0
    DOI: 10.1007/s43069-022-00140-0
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    References listed on IDEAS

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    1. Kwang-Il Kim & Keon Myung Lee, 2018. "Dynamic Programming-Based Vessel Speed Adjustment for Energy Saving and Emission Reduction," Energies, MDPI, vol. 11(5), pages 1-15, May.
    2. Stefan Kuhlemann & Kevin Tierney, 2020. "A genetic algorithm for finding realistic sea routes considering the weather," Journal of Heuristics, Springer, vol. 26(6), pages 801-825, December.
    3. Stefan Kuhlemann & Kevin Tierney, 2020. "Correction to: A genetic algorithm for finding realistic sea routes considering the weather," Journal of Heuristics, Springer, vol. 26(6), pages 827-827, December.
    4. Meng, Qiang & Du, Yuquan & Wang, Yadong, 2016. "Shipping log data based container ship fuel efficiency modeling," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 207-229.
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