This paper proposed a composite sandwich structure containing multilayer honeycombs, and a multi-objective optimization model containing its load-bearing and wave-absorbing properties, which were correlated with the geometric parameters of the honeycomb, was developed. The critical elastic buckling load was performed as an indicator to characterize the load-bearing capacity, and the bandwidth of the sandwich was employed as an indicator to characterize the wave-absorbing characteristics. This multi-objective optimization model was optimized based on JAYA algorithm and the results showed that the optimized structure had a significant improvement in both load-bearing and wave-absorbing capacities compared to the original structure.

In this paper, a new optimisation method incorporating lamination parameters and a guide-based blending model is proposed. Lamination parameters for a guide laminate and ply number of each panel are employed as design variables for optimisation with a parallel real-coded genetic algorithm incorporating structure behaviour and manufacturing constraints. During the optimisation process, with a form of least squares fitting adopted, another genetic algorithm is used to obtain the guide stacking sequence of the guide laminate from the guide lamination parameters, and then the laminate configurations of each panel are obtained from the guide stacking sequence and number of plies for each panel. The proposed framework is demonstrated via design of an 18-panel horseshoe configuration, where each panel is optimised individually with a buckling constraint. Numerical results indicate that the present algorithm is capable of obtaining fully blended designs.