An analytical–genetic algorithm approach for buckling load optimization of composite cylindrical shells under axial compression

The design of unstiffened thin-walled cylindrical shells under axial compression remains a critical aspect of lightweight thin-walled structures, as these components must sustain prescribed compressive loads without premature buckling, which can drastically reduce their load-carrying capacity and stiffness. Composite materials present an excellent alternative material that could help improve the strength of cylindrical shells when tailored properly as compared to their metal counterparts. However, the optimization of composite cylindrical shells presents a major challenge due to the complex interaction between laminate parameters such as ply orientation, stacking sequence, and material anisotropy, all of which significantly influence their buckling response. The main objective of this study is to develop a computationally efficient optimization framework that maximizes the critical buckling load of laminated composite cylindrical shells through optimal stacking sequence design. The analytical solution of the buckling stress was first derived utilizing the computational capabilities of Mathematica software. It is expressed in terms of laminate parameters. Then, a Genetic Algorithm implemented in Python was employed to determine the optimal laminate configuration. Analysis revealed that the optimized stacking sequences obtained through the proposed framework yielded comparable critical buckling loads compared to baseline and conventional layups, exhibiting strong agreement with benchmark analytical and finite element results from the literature. The findings reveal that integrating analytical modelling with evolutionary optimization provides a reliable and efficient design approach for enhancing the buckling performance of composite cylindrical shells, offering practical value in the design of advanced lightweight aerospace structural components.