Traditional designs of viscous dampers for large-span cable-stayed bridges often suffer from low efficiency and challenges in balancing multiple， mutually constrained damping control objectives. To address these issues， this paper proposes an improved multi-objective particle swarm algorithm for optimal damper parameters design， based on the "variational" method of genetic algo? rithms. A finite element model of a large span cable-stayed bridge was established， and a seismic response analysis of the entire bridge was conducted. Viscous dampers were installed in the longitudinal direction of the bridge according to the seismic demand. Response surface mathematical models were established to represent the relationships between the seismic responses of the tower bottom bending moment， damping force， beam end displacement， and the damper parameters. Using the seismic response surface model， a global automatic optimization search analysis of the damper parameters was performed using the proposed algorithm， re? sulting in the determination of the optimal damper parameters. Additionally， a set of damping parameter combinations were deter? mined for comparative analysis using the traditional parameter sensitivity analysis method. The results show that the optimization method offers good computational accuracy， high optimization efficiency， and a better trade-off among multiple， mutually con? strained seismic control objectives. The combination of damper parameters obtained by the optimization algorithm， compared to the damping response of the combination of damping parameters obtained by the conventional method， increases the bottom bend? ing moment of the tower by 1.73%， reduces the damping force by 5.97%， and reduces the displacement of the beam end by 1.66%. The optimized parameter combinations of dampers with higher accuracy are determined without the need for multiple finite element trial calculations， resulting in improved damping effect and significant time savings.