Multi-Objective Dynamic Induction Research of Ship Routes in the Context of Low Carbon Shipping

To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national “dual-carbon” strategy, a multi-objective ship route induction model is proposed. Considering the energy-saving and environmental issues of ships, this study aims to improve the transportation efficiency of ships by providing a ship route induction method. Ship data from a certain bay during a defined period are collected, and an improved backpropagation neural network algorithm is used to forecast ship traffic. On the basis of the forecasted data and ship route induction objectives, dynamic programming of ship routes is performed. Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55% compared with statically induced routes. This method has promising engineering applications in improving ship navigation efficiency, promoting energy conservation, and reducing emissions.