The fuel consumption of a ship during navigation is closely related to its speed, path and encountered weather. Ship operating companies always tend to choose the appropriate weather route for fuel consumption saving. When completing a voyage mission, the operating ships are always constrained by the estimated time of arrival (ETA). Under the condition that the total sailing time remains unchanged, different routes will correspond to different speeds. Therefore, for operating ships, the selection of weather route is always a coupling optimization problem of route and speed aimed at minimizing fuel consumption. In this paper, a model for a simultaneous determination of ship`s path and speed with the constraint of ETA is established. The rhumb algorithm is applied to generate path taking in account the influence of the curvature of the earth. The marine environment forecast data provided by a commercial weather forecast company is used to interpolate the weather encountered by ships in different route speed combinations. Subsequently, a self-developed fuel consumption model, which is recognized by operating companies, is applied to calculate the total fuel consumption for the whole voyage. Finally, the optimal path and speed are determined simultaneously by particle swarm optimization (PSO) algorithm. The result shows that the optimized route can reduce fuel consumption by 1.2% compared with great circle route. Besides, the optimized route makes ship avoid the rough sea conditions effectively.


Shipping is the most important form of transportation in international trade but also a huge fuel consumer. Planning a best route based on weather forecast and specific ship characteristics is an effective way to reduce fuel consumption. This best route is called as weather route (Padhy et al., 2008; Shao et al., 2012). Generally, the route is planned by the chief mate and confirmed by the captain. In most cases, the route is decided by their experiences, which is not the best choice sometimes (Lee et al., 2018). Therefore, it is of great practical significance to develop a route planning algorithm meeting the needs of navigation.

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