绿色能源双体无人艇艇型综合优化分析

Comprehensive optimization analysis of green energy catamaran unmanned craft

为了实现绿色能源双体无人艇的艇型最优设计,本文对艇型设计的多目标策略和智能优化算法进行研究。首先综合考虑太阳能和风帆以及快速性、操纵性、耐波性和抗倾覆性四大性能对艇型设计的影响,建立综合优化数学模型;然后基于遗传算法改编的综合优化设计软件确定总目标函数最优情况下的遗传次数、种群规模、变异概率和交叉概率;最后采用外部分层策略对遗传算法结合粒子群和混沌算法,进行了混合算法的比较分析。结果表明,相比于单一遗传算法,混合算法的优化效果更好,且在不同载波概率情况下,遗传算法+粒子群算法的优化效果均为最佳,外部分层策略可以有效提高寻优效果。

In order to achieve the optimal design of the green energy catamaran unmanned craft, this paper studies the multi-objective strategy and intelligent optimization algorithm of unmanned craft type design. Firstly, a comprehensive optimization mathematical model is established by comprehensively considering the influence of solar energy and sail and the four performances of fastness, maneuverability, wave resistance and overturning resistance on the design of the craft type;Then the unmanned craft comprehensive optimization software based on genetic algorithm was used to determine the genetic times, population size, mutation probability and crossover probability under the optimal condition of the total objective function;Finally, the external hierarchical strategy was used to compare and analyze the hybrid algorithm combining genetic algorithm with particle swarm optimization and chaos algorithm.The results show that: compared with the single genetic algorithm, the hybrid algorithm has better optimization effect. In the case of different carrier probability, the optimization effect of the genetic algorithm + particle swarm algorithm is the best. The external layering strategy can effectively improve the optimization effect.