Matching optimization of ship engine propeller and net for the trawler based on genetic algorithm

Abstract

Matching performance of ship engine propeller and net has a significant impact on propulsion efficiency for the trawler. In this paper, an improved genetic algorithm (GA) based on the particle swarm algorithm (PSO) is developed for matching optimization of ship engine propeller and net. Based on ship theory, the matching performance of ship engine propeller and net is analyzed. Considering the angular speed, picth ratio and disk ratio of propeller, a mathematical model is constructed in which the open-water propeller efficiency is taken as the objective function for matching optimization of ship engine propeller and net. The improved GA is presented to solve it, in which the PSO operator is introduced to the GA for the diversity of populations. The effectiveness of the approach is illustrated by a matching optimization example of ship engine propeller and net for the trawler.