Nonlinear dynamic instability and multi-objective design optimization of the GPLR-FGP plate under biaxial impacts

This paper investigates the nonlinear dynamic buckling and addresses the multi-objective design optimization of graphene platelets reinforced functionally graded porous (GPLR-FGP) composites under biaxial impacts, for the first time. Multifaceted influential effects on nonlinear instability and dynamic impulse resistance have been incorporated and examined meticulously. Two new multi-objective optimization algorithms, viz., Multi-objective Poplar Optimization Algorithm (MOPOA) and Adaptive Learning Multi-objective Poplar Optimization Algorithm (ALMOPOA), have been developed and innovatively proposed respectively, for composite design optimization. The MOPOA extends the state-of-the-art Poplar Optimization Algorithm to multi-objective problems. Through further ameliorating the MOPOA, the ALMOPOA is proposed incorporating manifold advisable strategies and novel improvements. Through the proposed framework, the multi-objective optimal designs of the GPLR-FGP composite have been established in forms of the Pareto front, with maximized nonlinear dynamic performance, impact carrying capacity, and contradictorily minimized structural weight. In numerical studies, the ALMOPOA is compared against the competitive existing optimization algorithms, revealing superior advantages with more surpassing optimal composite designs, more desirable convergence rates and diversity attributes.