Antenna optimization using combination of random and Nelder-Mead simplex algorithms

We present a relatively simple and robust algorithm for finding optimal and near optimal solutions for antenna design based on a combination of random and Nelder-Mead simplex algorithms. We considered the design of a Yagi-Uda antenna, as an example, for two reasons: it has many near optimal solutions; analysis of such an antenna is relatively quick. The presented combinations of random and Nelder-Mead methods are relatively simple and robust optimization algorithms. They can be advantageous in situations where the error function (the difference between the given criteria and the found solution) has many local minima of approximately the same depth or when formulation of the error function is complicated due to multiple involved criteria. Insight into near optimal solutions, which could be easily found using the proposed methods, offers more freedom in antenna design.