Structural Efficiency Enhancement in Steel Trusses utilizing Genetic Algorithm

This study presents an optimization approach for the topology and sizing of steel truss structures utilizing the Genetic Algorithm (GA). The objective is to minimize the weight of trusses while ensuring structural integrity by satisfying stress, displacement, and buckling constraints defined by the American Institute of Steel Construction (AISC) standards. The GA method is applied to various truss configurations, including 3-, 5-, 9-, 13-, and 17-member designs, under single and triple concentric load conditions. The results are compared with those from the ETABS software, demonstrating that the GA achieves substantial weight reduction. For instance, a 36% reduction is observed in the 3-member single-load truss, and a 31% reduction in the 9-member single-load truss compared to ETABS. Additionally, the GA enhances structural efficiency by optimizing truss topology and showcases flexibility in managing both discrete and continuous design variables. These findings underscore the reliability and effectiveness of GA in achieving significant weight savings and performance improvements in steel truss design.