Today there are many algorithms to solve optimization problems. In the meantime, meta-heuristic algorithms have been faced with the popularity of researchers. Over the past three decades, there are many meta-heuristic algorithms. The presentation of each of these algorithms may be randomly implemented by other researchers in solving various problems of science. The Football Game Algorithm(FGA) is also proposed as a new meta-heuristic algorithm based on simulating the behavior of football players during a game to find the best mode for scoring goals under the supervision of the coach. In the present research, for the first time, this algorithm has been investigated in civil engineering structures including cantilever beam as a benchmark structure and compared to the results of the powerful particle swarm optimization algorithm and the constrained minimization of the toolbox of MATLAB. Also, because of the random intrinsic nature of the algorithms used in the research, for the statistical study of the structure of the benchmark structure, 30 times have been performed to investigate the sensitivity of their response. The results show that in spite of the random nature of the algorithm, the objective function changes are not tangible. After optimizing the size of the benchmark structure, it was found that savings of 8% to 70% The computational time ability of the algorithm to determine the absolute optimal response and the lower sensitivity to the random nature of the algorithm is dependent on the features of the FGA in relation to the PSO ones.