Plasma Generation Optimization (PGO) is a newly developed meta-heuristic algorithm that is inspired by the process of plasma generation. This study attempts to enhance the performance of the PGO in order to improve solution accuracy, reliability, and convergence speed. The new method, called improved plasma generation optimization (IPGO), is tested on a benchmark structural optimization problem. Then, the optimal design of reinforced concrete (RC) frames is performed using the PGO and IPGO algorithms. The variables of the problem are taken as the geometry of the cross-sections and reinforcing bars of the members. These variables are considered discrete and are selected from a predetermined section database (DB). The objective function consists of the construction material costs of the structural elements. The plannar frames with different stories are designed according to the standards and requirements of the American Concrete Institute’s Building Code (ACI 318-8). Time history analysis is used to analyze the structures. The main goal of the optimization is to find the most economical design of the frame structure under strong seismic actions. The results show that the proposed approach is feasible to find the optimum design of the structural members of RC frames and the IPGO algorithm is more competent than the PGO algorithm.