<p>In this research, a practical strategy for identifying the structural characteristics (i.e., stiffness, mass, and damping coefficients) is developed based on the Fire Hawk Optimization (FHO) algorithm. The main objective is to investigate the performance of the FHO algorithm in time-domain system identification problems. To provide a comprehensive comparison, 12 additional optimization algorithms are assessed. The proposed time-domain approach employs finite element model updating based on limited vibration data measured from the structural responses. In this regard, the system identification problem is formulated as an unconstrained optimization problem with the objective function of minimizing the mean square error between the simulated acceleration responses and the measured ones. Unlike the frequency-domain methods, the nonlinear system identification can be performed using time-domain methods, too. For the sake of validation, the performance of the FHO algorithm is evaluated through both numerical and experimental cases. The numerical examples consist of 36 cases varying in signal durations, noise levels, and the number of degrees of freedom under both known and unknown mass conditions. Furthermore, a five-story steel shear building is considered for the experimental validation. Finally, the comparative study indicates the superior ability of the FHO algorithm in solving both practical and numerical system identification problems. The FHO algorithm effectively minimized errors and accurately identified system parameters, demonstrating its capability as a highly effective tool for structural system identification in the time-domain.</p>