Buckling Load Maximization of Composite Laminates Using Particle Swarm Optimization With Various Constraints

The stacking sequence of composite laminates is designed to have maximum buckling load using the particle swarm optimization (PSO) algorithm. The original PSO algorithm is modified to handle the discrete ply angles and the constraints such as stiffness and 4-ply contiguity requirements. For this, the augmented Lagrange multiplier (ALM) method is incorporated into the PSO algorithm. For the verification of the algorithm, the benchmarking problems are solved and the results are compared with the ones from the genetic algorithm or the analytic solutions. And then the laminates under in-plane compressive loadings are optimized for maximum buckling load considering the various constraints. The numerical results show that the algorithm finds the optimum with relatively small number of iterations with satisfying the constraints explicitly. Considering its advantage of derivative-free and simple procedures, the proposed algorithm can be applied to more complex models coupled with finite element analysis and various constraints.