| Abstract: | Maritime transportation has become an important part of the international trade system. To promote its sustainable de-velopment, it is necessary to reduce the fuel consumption of ships, decrease navigation risks, and shorten the navigation time. Ac-cordingly, planning a multi-objective route for ships is an effective way to achieve these goals. In this paper, we propose a multi-ob-jective optimal ship weather routing system framework. Based on this framework, a ship route model, ship fuel consumption model, and navigation risk model are established, and a non-dominated sorting and multi-objective ship weather routing algorithm based on particle swarm optimization is proposed. To fasten the convergence of the algorithm and improve the diversity of route solutions, a mutation operation and an elite selection operation are introduced in the algorithm. Based on the Pareto optimal front and Pareto optimal solution set obtained by the algorithm, a recommended route selection criterion is designed. Finally, two sets of simulated navigation simulation experiments on a container ship are conducted. The experimental results show that the proposed multi- objec-tive optimal weather routing system can be used to plan a ship route with low navigation risk, short navigation time, and low fuel consumption, fulfilling the safety, efficiency, and economic goals. |
