A Study on Hybrid of Genetic Algorithm and Evolution Strategy for Antenna Design

This paper proposes a hybrid algorithm based on Genetic Algorithm (GA) and Evolution Strategy (ES). The GA is not successful in searching an optimal solution in the view point of convergence speed and solution quality. The ES has the risk of being trapped in a local minimum. The hybrid algorithm is composed of GA and ES in order to make up for these defects of GA and ES. The procedure of searching an optimal solution in hybrid algorithm is as follows. Firstly, the vicinity of optimal solution is reached by using the GA. And then the ES is used to find an accurate optimal solution. In terms of the convergence rate, the proposed hybrid algorithm is compared with the GA using the optimal design of 2.45 GHz CPW-fed circularly polarized antenna. The results of the antenna optimized using GA and hybrid algorithm satisfy the objective value. The convergence rate graph shows that convergence rate of GA decreases and ES rapidly searches optimal solution in the vicinity of optimal solution after 380 iterations.