Abstract: The optimal design of composite laminates is crucial for improving the bearing capacity of aircraft structures. In this paper, based on the genetic algorithm and the random normal distribution optimization algorithm, taking the buckling load of the axial compression composite laminates as the objective function, the optimal design of the layer sequence is carried out. Two optimization algorithms are programmed in MATLAB language to optimize the layer sequence of symmetrical balanced laminates with different layers and boundary conditions. The results show that the genetic algorithm with integer coding and penalty function can be used to optimize the sequence of laminated plate. For the 24-layer plates with pinned and fixed constraints, the failure loads of the optimal layers are increased by 27% and 15% than those of the worst layers, which demonstrates the obvious optimal effect. The results from the random normal distribution optimization algorithm are consistent with those from the genetic algorithm. Since the random normal distribution optimization algorithm is concise and easy to converge, it is more suitable for the optimal design of composite laminates in practice.

Key words: composite, laminates, layer optimization, genetic algorithm, random normal distribution