Multi-Objective Weather Routing Algorithm for Ships Based on Hybrid Particle Swarm Optimization

Maritime transportation has become an important part of the international trade system. To promote its sustainable development, it is necessary to reduce the fuel consumption of ships, decrease navigation risks, and shorten the navigation time. Accordingly, planning a multi-objective route for ships is an effective way to achieve these goals. In this paper, we propose a multi-objective 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-objective 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.