This study introduces an energy-based optimization framework to enhance the seismic performance of steel moment-resisting frames (SMRFs) through the strategic placement and parameter tuning of viscous dampers. A modified binary-real particle swarm optimization (BRPSO) algorithm is utilized to simultaneously determine the optimal distribution of dampers across building stories and to identify their corresponding damping coefficients and velocity exponents. The optimization objective focuses on maximizing the ratio of energy dissipated by the dampers to the total input seismic energy, while strictly adhering to structural constraints, such as permissible interstory drift limits. The proposed methodology is validated through nonlinear time-history analyses of six- and ten-story SMRFs modeled in OpenSees, subjected to Kanai–Tajimi filtered white noise excitations. Numerical results demonstrate that the optimized damping system significantly mitigates seismic demand; specifically, it reduces hysteretic energy by over 99.11% and input energy by approximately 12.12% in the six-story frame, with even more pronounced improvements (up to 100% reduction in hysteretic energy and 34.93% in input energy) observed in the ten-story structure. Furthermore, the analysis reveals a threshold effect where exceeding the optimal number of dampers yields diminishing returns on seismic performance while increasing construction costs. The findings confirm that the proposed method provides an efficient and robust solution for optimizing viscous damping systems in steel structures.