The Microstructure Design Optimization of Negative Index Metamaterials Using Genetic Algorithm
In recent years, metamaterials have been the subject of research interest for many investigators worldwide. However, most of reported metamaterial microstructures are obtained based on human intuition, experience or large numbers of simulation experiments which were time-consuming, ineffective or expensive. In this paper, we propose a novel negative index metamaterial microstructure design methodology that uses a FDTD solver optimized by genetic algorithm (GA) technique in order to achieve a simultaneously negative permeability and permittivity. Firstly, an novel genetic algorithm optimization model for wide frequency band of negative refraction was proposed. Then the effectiveness of the new technique was demonstrated by a microstructure design example that was optimized by GA. By using numerical simulations techniques and S-parameter retrieval method, we found that the GA-designed optimal solution can exhibit a wide LH frequency band with simultaneously negative values of effective permittivity and permeability. Therefore, the design methodology presented in this paper is a very convenient and efficient way to pursue a novel metamaterial microstructure of left-handed materials with desired electromagnetic characteristics.