This study proposes a novel approach for the optimal design of tuned mass dampers (TMDs) and multiple tuned mass dampers (MTMDs) to minimize the seismic response of structures. The optimization is performed using a hybrid combination of Tabu Search and Particle Swarm Optimization algorithms, applied within a single-objective framework. In this method, the algorithms are used individually to optimize the parameters of a single TMD and jointly to tune multiple dampers working in parallel within an MTMD system. This hybrid strategy enables a more precise and efficient evaluation of damper performance. Tuned mass dampers are effective devices that absorb vibration energy induced by earthquakes and enhance the dynamic response of buildings. Their performance strongly depends on the accurate tuning of key parameters mass, stiffness and damping making parameter optimization a crucial step in their design. The case study considers a 10-story linear building model as a benchmark for evaluating the performance of both TMD and MTMD systems. The optimization aims to reduce three main structural responses: roof displacement, roof acceleration, and inter story drift. To simulate realistic conditions, two earthquake records are used the 1940 El Centro and 1995 Kobe earthquakes. The results show that optimally tuned TMDs and MTMDs effectively reduce displacements and drifts, while their effect on acceleration reduction is comparatively smaller, though still beneficial. Overall, the proposed optimization method achieves a 15–35% reduction in the objective functions under different earthquake scenarios, demonstrating the capability of hybrid metaheuristic algorithms to enhance structural performance through well-tuned damper systems.