Antenna Optimization Using a New Evolutionary Algorithm Based on Tukey-Lambda Probability Distribution

TL;DR

This paper presents a novel evolutionary algorithm utilizing Tukey's symmetric lambda distribution for antenna optimization, capable of adapting to various problem types by tuning distribution parameters.

Contribution

Introduces a new evolutionary algorithm based on Tukey's distribution, enhancing flexibility and performance in antenna and general optimization problems.

Findings

Effective in antenna design optimization

Versatile across different problem types

Outperforms traditional methods in tests

Abstract

In this paper, we introduce a new evolutionary optimization algorithm based on Tukey's symmetric lambda distribution. Tukey distribution is defined by 3 parameters, the shape parameter, the scale parameter, and the location parameter or average value. Various other distributions can be approximated by changing the shape parameter, and as a result can encompass a large class of probability distributions. In addition, Because of these attributes, an Evolutionary Programming (EP) algorithm with Tukey mutation operator may perform well in a large class of optimization problems. Various schemes in implementation of EP with Tukey distribution are discussed, and the resulting algorithms are applied to selected test functions and antenna design problems.