Ship route planning based on intelligent mapping swarm optimization

In this paper, we propose a new strategy for simultaneously optimizing ship route and speed using a hierarchical mapping method that takes into account different carbon tax models. Compared with the traditional route planning methods, the main novelty of the proposed method is to separate the decision-making and weather information layers, which allows us to directly obtain the ship route and speed decision plan that conform to the ship's maneuverability and crew habits. The key algorithmic contribution is a bi-layer mapping intelligent optimization algorithm, which establishes the mapping relationship between the upper and lower layers and a synchronous iterative update strategy. Case studies show that the designed method has significant advantages in both conventional and complex terrain ocean scenarios. Moreover, the sensitivity analysis showed that the proposed method can help shipping companies to better cope with rising fuel prices and various ship carbon tax models.

Automated summary

In this paper, a new strategy for simultaneously optimizing ship route and speed is proposed using a hierarchical mapping method that considers different carbon tax models. The main innovation of the proposed method is the separation of decision-making and weather information layers, which allows for the direct acquisition of ship route and speed decisions that align with maneuverability and crew habits. The key algorithmic contribution is a bi-layer mapping intelligent optimization algorithm, which establishes mapping relationships and a synchronous iterative update strategy. Case studies demonstrate significant advantages in both conventional and complex terrain ocean scenarios. Furthermore, sensitivity analysis shows that this method can help shipping companies better cope with rising fuel prices and various ship carbon tax models.