Comparative Study on Search Performance Between GA and PSO for Stacking Optimization of Laminated Plates - Michio Innami; Yoshihiro Narita (EPI International Journal of Engineering, 2018)
This paper deals with the optimization problem to maximize the vibration performance of laminated composite plates by properly tailoring the fiber orientation angles in the layers. The optimization is performed by using two metaheuristic methods, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), and comparison is made to evaluate differences in search performance of the two methods. Test problems are set for the evaluation of maximizing the fundamental frequencies, and some parameters are properly tuned for efficient solution search. From the numerical experiments, it turned out that the search using PSO indicates faster convergence and better solutions than GA scheme under assumption of search domain in real number.