Study on Matching Design of Ship Engine and Propeller Based on Improved Moth-Flame Optimization Algorithm
This paper develops an improved moth-flame optimization(IMFO)algorithm for the ship propeller-matching problem,which comprehensively considers propeller efficiency,cavitation,and strength for two existing ships as calculation examples.Ge-netic algorithm(GA)and the original moth-flame optimization(MFO)algorithm are used as comparison algorithms to analyze the performance of the IMFO-assisted propeller-matching task.Numerical experiment results show that the convergence time of the IMFO algorithm in solving the propeller-matching problem is reduced by 44.24％and 54.14％compared to the GA algorithm in the two examples,and by 23.9％and 23.12％compared to the MFO algorithm,respectively.In addition,in terms of solution ac-curacy,the IMFO algorithm is slightly better than the GA and MFO algorithms in calculation example 1.In calculation example 2,the IMFO algorithm is improved by 3.66％compared to the GA algorithm and by 0.98％compared to the MFO algorithm.Fi-nally,by visualizing the feasible solution space of the two examples,the performance of the IMFO algorithm is further discussed.The above results demonstrate that the IMFO algorithm has strong global search capability and is competitive and robust in sol-ving the propeller-matching problem.
Improved moth-flame optimization algorithmOptimized designSwarm intelligence optimization algorithmMatching of ship engine and propellerMarinepropeller
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