四边形的
堆积
差异进化
最优化问题
算法
数学优化
稳健性(进化)
全局优化
计算机科学
数学
工程类
有限元法
结构工程
生物化学
化学
物理
核磁共振
基因
作者
Weiping Wang,Qingshan Wang,Rui Zhong,Longting Chen,Xianjie Shi
标识
DOI:10.1016/j.compstruct.2023.116764
摘要
A Hybrid Whale Optimization Algorithm (HWOA) is proposed to optimize the stacking sequence of arbitrary quadrilateral composite plates. By introducing an adversarial learning strategy, a broader search is performed on the initial domain to generate a better initial population. The mutation operator and opposition-based learning (OBL) strategy of the differential evolution (DE) algorithm are combined to maintain the diversity of the evolutionary process. In addition, the nonlinear convergence factor is introduced to improve the global exploration ability of HWOA when dealing with discrete problems. The stacking sequences of quadrilateral composite plates with different boundary conditions and geometries are optimized to maximize the fundamental frequency. The optimized results of HWOA are compared with those of whale optimization algorithm (WOA), Aquila optimizer (AO), artificial bee colony (ABC) algorithm, DE algorithm and layerwise optimization approach (LOA) algorithm. The results show that HWOA with multiple strategy combinations has good global search capability and robustness, and thus HWOA is a good candidate optimization algorithm for composite plate optimization.
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