Basic and Improved Sine–Cosine Optimization Algorithms for Antenna Design

In this paper, a new optimization algorithm, Sine–Cosine Algorithm (SCA), is introduced for the antenna community. The SCA is a recently proposed metaheuristic algorithm based on the sine and cosine functions. This algorithm has a simple structure and searches the solution space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality results. Moreover, an improved version of SCA is presented that reduces the probability of getting stuck in local optima. ISCA is evaluated to optimize seven benchmark functions and is shown to be better. Then, we apply ISCA in designing a reconfigurable antenna. The comparison of the performance of SCA/ISCA algorithms with those of the GA, PSO, and TLBO demonstrates the ability of these algorithms in terms of the better performance and faster convergence. For validation and clarification, a reconfigurable antenna prototype that consists of slots on the ground plane and a PIN diode is fabricated and tested. The measured and simulated results are found in good agreement.