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Reanalysis assisted metaheuristic optimization for free vibration problems of composite laminates

机译:重新分析辅助元启发式优化解决复合材料层合板的自由振动问题

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摘要

The metaheuristic optimization methods have been widely used in complex composite material design. However, it is still difficult to apply these methods to complicated problems due to expensive cost of evaluations. Therefore, to reduce the expensive cost of finite element (FE) analysis in the composite laminate optimization problems, the surrogate assisted optimization (SAO) method has been well developed. However, considering the low accuracy of surrogate model for complicated cases, the SAO is always difficult to converge to the global optimum. In this study, a fast and accurate solver, the reanalysis algorithm is extended to vibration problem and integrated to improve the efficiency of metaheuristic optimization of composite laminates instead of surrogate model. In the proposed method, the shifting method is used in each iterative step. To validate the performance of suggested method, several numerical examples are presented. The results demonstrate that reanalysis assisted particle swarm optimization (RPSO) is much more efficient for free vibration problems of composite laminates than the PSO. Moreover, such strategy can be extended to other metaheuristic algorithms easily.
机译:元启发式优化方法已广泛用于复杂的复合材料设计中。然而,由于昂贵的评估成本,仍然难以将这些方法应用于复杂的问题。因此,为了减少复合材料层压板优化问题中有限元(FE)分析的昂贵成本,替代辅助优化(SAO)方法已经得到了很好的发展。但是,考虑到复杂情况下代理模型的准确性较低,SAO始终很难收敛到全局最优值。在这项研究中,作为一种快速,准确的求解器,重新分析算法被扩展到振动问题,并被集成以提高复合材料层板的超启发式优化的效率,而不是替代模型。在提出的方法中,在每个迭代步骤中都使用了移位方法。为了验证所建​​议方法的性能,给出了几个数值示例。结果表明,与PSO相比,再分析辅助粒子群优化(RPSO)对复合材料层合板的自由振动问题要有效得多。而且,这种策略可以容易地扩展到其他元启发式算法。

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