Applying an improved particle swarm optimization algorithm to ship energy saving - Du, Wei; Li, Yanjun; Shi, Jianxin; Sun, Baozhi; Wang, Chunhui; Zhu, Baitong (Energy (Oxford), 2023)
Due to the increasingly competitive maritime market and stringent regulatory requirements, the optimization of ship energy efficiency is attracting more and more attention. The energy efficiency of ship navigation is affected by many factors such as ship structure, crew operation and navigation environment. In this paper, the proposed improved second-order oscillating PSO algorithm is used to study the ship energy efficiency from the viewpoint of route optimization by considering the sea conditions and constraints. Firstly, a nonlinear optimization model for ship FOC (fuel oil consumption) considering the time-varying sea state is established. On this basis, the energy efficiency and economic benefits are analyzed in terms of multiple indicators e.g., FOC and CO2 emissions per unit distance and per unit mass of freight. Finally, the energy saving potential of the method is demonstrated with an example of an oil tanker. The results show that both FOC and emissions are reduced after optimization, and energy efficiency and economy are improved by 1.17% and 2.55%, respectively. This indicated that the considerable effect of the proposed method applied to ship energy saving optimization. •Ship route optimization achieves a cost-efficient way to save energy on ships.•Improved particle swarm optimization algorithm with high accuracy and stability.•Well-established constraints ensure the feasibility of the optimization solution.•Ship energy saving drives maritime industry to green development.