Fireworks algorithm (FWA) is an artificial intelligence algorithm developed by emulating the burst process of fireworks. This paper applies a modified version of fireworks algorithm called MoFWA to design disparate steel trusses and planar frames. In this study, the objective is to improve FWA’s performance by adding two operators to it: 1) fly-back mechanism 2) duplicate spark remover operator. Also, its amplitude is changed into a dynamic one to enhance its compatibility with different optimization problems. The function we are focusing on is the total weight of the structure. This takes into account the requirements for serviceability and strength as outlined by the American Institute for Steel Construction's Load and Resistance Factor Design (LRFD) standards. A total of six benchmark structures including a 10-bar truss, a 25-bar truss, a 582-bar tower truss, a two-bay three-story frame, a one-bay 10-story frame, and a three-bay 24-story frame are chosen from previous studies for the optimization. In addition, a comparison is presented between the results of MoFWA with FWA and other optimization methods such as modified sine-cosine algorithm (MSCA), newton meta-heuristic algorithm (NMA), improved grey wolf optimizer (GWOM), enhanced whale optimization algorithm (EWOA), switching teams algorithm (STA), MHBMO, artificial bee colony (ABC), school-based optimization (SBO), teaching-learning based optimization (TLBO), design-driven harmony search (DDHS), and inscribed hyperspheres (IHS). The results indicate that MoFWA is completely better than FWA and can generate superior optimal solutions compared to the other optimization algorithms.