A comparative study on the metaheuristic-based optimization of skew composite laminates

Plate structures are the integral parts of any maritime engineering platform. With the recent focus on composite structures, the need for optimizing their design and functionality has now been tremendously realized. In this paper, a comprehensive study is carried out on the effectiveness and optimization performance of three metaheuristic algorithms in designing skew composite laminates under dynamic operational environments. The natural frequencies of the composite panels are measured using a first-order shear deformation theory-based finite element (FE) approach. The stacking sequence of the composite panels is optimized so that the natural frequency separation between the first two modes is maximized. The three metaheuristics considered here are genetic algorithm (GA), repulsive particle swarm optimization with local search and chaotic perturbation (RPSOLC), and co-evolutionary host-parasite (CHP) algorithm. It is observed that in general, the FE-coupled metaheuristic algorithms are quite capable to significantly improve the baseline designs. In particular, FE-CHP algorithm outperforms both the FE-GA and FE-RPSOLC algorithms with respect to accuracy, computational speed and solution reliability.