Meta-heuristic optimization algorithms for vibration and buckling analysis of laminated composite plates

The authors propose meta-heuristic optimization algorithms for the vibration and buckling analysis of laminated composite plates. This approach combines unified higher-order shear deformation theory, the Ritz method, and three optimization algorithms: the Shrimp and Goby Association Search Algorithm (SGA), Balancing Composite Motion Optimization (BCMO), and Differential Evolution (DE). The Ritz method, utilizing hybrid shape functions, is employed to solve optimization problems by using the Gram-Schmidt process to construct approximation functions. The SGA and BCMO are applied for the first time to determine the optimal buckling loads and frequencies of laminated composite plates. Numerical examples are provided to explore the influence of fiber angle, modulus ratio, and various boundary conditions on the optimal results. The findings demonstrate that BCMO and SGA are efficient and robust algorithms for addressing the optimization problems of laminated composite plates.