A Nonlinear Computational Framework for Optimizing Steel End-Plate Connections Using the Finite Element Method and Genetic Algorithms

The design of steel connections presents considerable complexity due to their inherently nonlinear behavior, cost constraints, and the necessity to comply with structural design codes. These factors highlight the need for advanced computational algorithms to identify optimal solutions. In this study, a comprehensive computational framework is presented in which the finite element method (FEM) is integrated with a genetic algorithm (GA) to optimize material usage in bolted steel end-plate joints, while structural safety is ensured based on multiple performance criteria. By incorporating both material and geometric nonlinearities, the mechanical response of the connections is accurately captured. The proposed approach is applied to a representative beam-to-column assembly, with numerical results verified against experimental data. By employing the framework, an optimized layout is obtained, yielding a 10.4% improvement in the overall performance objective compared to the best-performing validated model and a 39.3% reduction in material volume relative to the most efficient feasible alternative. Furthermore, a 53.6% decrease in equivalent plastic strain is achieved compared to the configuration exhibiting the highest level of inelastic deformation. These findings demonstrate that the developed method is capable of enhancing design efficiency and precision, underscoring the potential of advanced computational tools in structural engineering applications.