A multi-objective collaborative optimization method of ship energy efficiency based on NSGA-II and TOPSIS

To enhance ship navigation efficiency and minimize fuel consumption and emissions, this study proposes a multi-objective energy efficiency optimization method for ships under actual operating conditions. A comprehensive mathematical model integrating ship, engine, and propeller dynamics while accounting for sea-state influences is developed and validated using experimental data. Based on this model, optimization models for propeller parameters and navigation speed are established. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to generate the Pareto solution set, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach is utilized to identify the optimal solution. The results demonstrate that optimizing propeller parameters enhances the propulsion efficiency by 2.11%, reduces the specific fuel oil consumption (SFOC) by 1.93%, and reduces the nitrogen oxide (NOx) emissions by 12.91%. Furthermore, navigation speed optimization based on the refined propeller design yields a 3.05% reduction in the total fuel consumption and a 10.39% decrease in the total NO_x emissions when voyage time constraints are not considered, albeit with a 3.57% increase in total navigation duration. Under voyage time constraints, the total fuel consumption and the total NO_x emissions are reduced by 1.97% and 8.31%, respectively, while total navigation time decreases by 2.92%. These findings indicate that the proposed multi-objective optimization method based on NSGA-II and TOPSIS effectively enhances ship energy efficiency and environmental performance. By integrating operational and design parameter optimization while simultaneously addressing economic and ecological considerations, this study offers valuable insights for advancing ship energy efficiency strategies.