Shear walls are crucial for seismic resistance in mid- and high-rise buildings, but they are prone to bending deformation, particularly in upper floors during earthquakes. Previous studies have suggested curtailing shear walls at specific levels to optimize their performance; however, upper frames without shear walls still suffer from significant deformation. Buckling-Restrained Braces (BRBs) can enhance seismic resistance by increasing shear capacity, especially in floors without shear walls. Determining the optimal number and placement of BRBs, however, remains a challenging issue. This study addresses this gap by comparing metaheuristic methods, specifically Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), for optimizing BRB placement and number in reinforced concrete frames with curtailed shear walls. These algorithms were selected for their ability to explore large solution spaces and identify near-optimal solutions efficiently. The optimization aims to minimize the number of BRBs, reduce the damage index of surrounding structural elements, and limit inter-story drift while remaining within drift limits. Weighting factors were applied to these parameters, and a trial-and-error approach was used to determine the most suitable values. A 2D model (x–z plane) was employed to reduce computational costs, with nonlinear dynamic analysis conducted using STERA_3D. Results indicate that for a 10-story model, GA suggested 19 BRBs and PSO suggested 21 BRBs. GA outperformed PSO in computational efficiency, offering faster convergence and more accurate BRB placement.