Optimization Design for Steel Trusses Based on a Genetic Algorithm

Abstract

Steel trusses are widely utilized in engineering structures, and their optimization is essential for enhancing structural performance and reducing material consumption. Existing optimization methods for steel trusses predominantly rely on the trial-and-error method, which is not only inefficient but also inaccurate. Therefore, this study focused on the optimization of steel trusses using an efficient and accurate optimization methodology. Based on a genetic algorithm and the finite element method, both mono- and multi-parameter optimization designs for steel trusses were executed, an applicable optimization design method for steel trusses was established, and corresponding optimization design programs were developed. The analysis demonstrates that the proposed optimization method effectively optimizes truss height and member cross-section, leading to a significant reduction in material consumption. Compared to the traditional trial-and-error method, the proposed optimization method exhibits adequate calculation accuracy and superior optimization efficiency, thereby providing a robust theoretical foundation for the engineering design of steel trusses.