针对层合板铺层优化问题，提出一种改进鲸鱼算法(IWOA)。通过引入对立学习策略保持进化过程的多样性，同时结合非线性收敛因子和自适应阈值提高IWOA的全局搜索能力；以层合板的铺设角度为设计变量、基频及带隙为优化目标进行板的频率优化，并使用Ritz法求解。基于IWOA算法对长宽比分别为1和2的复合材料矩形层合板进行优化研究，并与经典鲸鱼算法(WOA)、分层优化算法(LOA)和差分进化算法(DE)进行比较分析。结果表明，相较于LOA、DE和WOA算法，IWOA具有更好的全局收敛性，且在处理多模态问题时更具可靠性。
Abstract
An improved whale optimization algorithm (IWOA) is proposed for the laminate lay-up optimization problem. The diversity of the evolutionary process is maintained by introducing a contrastive learning strategy. The global search capability of IWOA is improved by combining a non-linear convergence factor and an adaptive threshold. The frequency optimization of the plate is carried out using the lay-up angle of the laminate as the design variable and the fundamental frequency and band gap as the optimization objectives, and is solved using the Ritz method. The optimization of composite rectangular laminates with aspect ratios of 1 and 2 are investigated based on IWOA and analyzed in comparison with the classical whale optimization algorithm (WOA), the layered optimization algorithm (LOA) and the differential evolution algorithm (DE). The results show that IWOA has better global convergence and is more reliable in dealing with multimodal problems compared to LOA, DE and WOA algorithms.
关键词
改进鲸鱼算法 /
复合材料 /
层合板 /
铺层角度 /
基频
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Key words
improved whale optimization algorithm /
compound material /
laminates /
layer angle /
fundamental frequency
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