In order to meet the development requirements of intelligent shipping and the domestication of meteorological navigation in China, a ship multi-objective route planning method based on the fusion of A* and non-dominated sorting genetic algorithm II (NSGA-II) is proposed that can adapt to complex and diverse long-distance navigation tasks.

By incorporating the A* algorithm into NSGA-II to guide the search direction and accelerate the convergence speed, an environmental data model and objective functions are constructed. Simulation verification is then performed using the trans-Pacific route.

The simulation results demonstrate that the proposed model and algorithm can obtain a uniformly distributed and diversified Pareto optimal route set. All routes can successfully avoid areas with severe weather conditions, and the most suitable route for the ship can be selected according to the decision-makers' needs.

In summary, the proposed method can be applied to optimize ship ocean routes under multiple constraint conditions and identify routes that meet the voyage objectives, thereby reducing operational costs, improving shipping efficiency and providing support for ship meteorological navigation and future intelligent ship navigation.