Hybrid optimization methods combine genetic and traditional algorithms to improve the efficiency of power systems. Genetic algorithms help with global searches, while traditional methods focus on local optimization. By using a new algorithm based on function transform and matrices, the researchers were able to optimize both discrete and continuous variables effectively. The hybrid approach proved to be practical and efficient in case studies.