Optimizing Aluminum Plate Thickness Using Different Optimization Algorithms

The study investigates the differences between three optimization algorithms: modified Evolutionary Structural Optimization (ESO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), for plate buckling optimization. The thickness distributions of the same thin aluminum plates were optimized for specific buckling shape and buckling load targets using the three algorithms, based on FEM linear buckling analysis. A discussion of the three methods is summarized from the optimization effects and computational resources. It is shown that the thickness distribution may be designed in such a way as to control the buckling behaviors, thereby maximizing the opening for building ventilation. The modified ESO method may be a good option to control the buckling of a plate. The PSO and GA are suitable for a quick buckling optimization.