Multiobjective Optimization of Functionally Graded Material Columns

M. Kasem, K. Maalawi
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引用次数: 1

Abstract

We developed a hybrid model for multiobjective optimization of composite structures. It is applied to find the optimal designs of slender, thin-walled, and functionally graded material (FGM) columns. The overall objective function is defined as the weighting sum of the dimensionless column mass $\widehat{M}_{s}$ and critical buckling load $\bar{P}_{cr}$, expressed as $f(\bar{x})=\alpha\widehat{M}_{s}(\bar{x})-(1-\alpha)\bar{P}_{cr}(\bar{x})$. Three global optimization algorithms i.e., the genetic algorithm (GA), sequential quadratic programming (SQP), and hybrid GA-SQP were employed to investigate the column best design point. Several optimization models are developed and the optimal designs are obtained.
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功能梯度材料柱的多目标优化
建立了复合材料结构多目标优化的混合模型。它被应用于寻找细长、薄壁和功能梯度材料(FGM)柱的最佳设计。总体目标函数定义为无因次柱质量$\widehat{M}_{s}$与临界屈曲载荷$\bar{P}_{cr}$的加权和,表示为$f(\bar{x})=\alpha\widehat{M}_{s}(\bar{x})-(1-\alpha)\bar{P}_{cr}(\bar{x})$。采用遗传算法(GA)、序列二次规划(SQP)和混合遗传-SQP三种全局优化算法对圆柱最佳设计点进行了优选。建立了几种优化模型,并进行了优化设计。
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