Multiobjective Optimization of Functionally Graded Material Columns

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.