with ever increasing load and insufficient growth of generation and transmission capacities, the operating constraints of modern integrated power system are increasing. It has led to ever increasing dynamic problems of low frequency oscillations in the system that needs to be detected and damped out quickly and efficiently. In electrical power networks small oscillations appear from time to time. These oscillations concern the quantities determining the equilibrium point of the system, and following which, system stability and system behaviors are influenced. The objective of our study is to check the static stability of the high voltage power to small perturbations of electrical network. In this context, after linearizing the system, power system stabilizer (PSS) has so far been extensively utilized to mitigate these problems. This paper presents a novel and efficient approach for the optimal tuning of power system stabilizer parameters (PSS) using a genetic algorithm (GA) with the eigenvalue-based objective function. The proposed approach is implemented and examined in a system with a single machine connected to an infinite bus via a transmission line. The results of this technique have been verified by eigenvalue analysis and time-domain simulations. The obtained results were evaluated and compared with ones obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulations demonstrated the effectiveness of the proposed approach in damping the electromechanical oscillations and enhancing the system dynamic stability.