Safe-economical route model of a ship to avoid tropical cyclones using dynamic forecast environment

Abstract

Abstract. In heavy sea conditions related to tropical cyclones (TCs), losses to shipping caused by capsizing are greater than other kinds of accidents. Therefore, it is important to consider capsizing risk in the algorithms used to generate safe-economic routes that avoid tropical cyclones (RATC). A safe-economic routing and assessment model for RATC, based on a dynamic forecasting environment, is presented in this paper. In the proposed model, a ship's risk is quantified using its capsizing probability caused by heavy wave conditions. Forecasting errors in the numerical models are considered in the ship risk assessment according to their distribution characteristics. A case study shows that: the economic cost of RATCs is associated not only to the ship's speed, but also to the acceptable capsizing probability which is related with the ship's characteristic and the cargo loading condition. Case study results demonstrate that the optimal routes obtained from the model proposed in this paper are superior to those produced by traditional methods.

A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping

“…Kang et al (2012) developed a maritime transportation planning support system by adopting a heuristic algorithm to achieve a ship's optimal sailing route. Wu et al (2013) established a safe-economical route model based on the dynamic prediction environment, which could determine the shortest route time-wise by combining the ocean's dynamic information and route feasibility analysis. Kim et al (2014a) proposed an angular rateconstrained path planning algorithm that is effective for global path planning of unmanned surface vehicles (USVs).…”