Genetic algorithm optimization for aerospace electromagnetic design and analysis

Abstract

This paper provides a tutorial overview of a new approach to optimization for aerospace electromagnetics known as the Genetic Algorithm. Genetic Algorithm (GA) optimizers are robust, stochastic search methods modeled on the concepts of natural selection and evolution. The relationship between traditional optimization techniques and GA is discussed and the details of GA optimization implementation are explored. The tutorial overview is followed by a number of applications in which GA has proved useful. The applications discussed include the design of lightweight, broad-band microwave absorbers, the reduction of array sidelobes in thinned arrays, the design of shaped beam antenna arrays, and the extraction of natural resonance modes of radar targets from the backscattered response data. Genetic Algorithm Optimization is shown to be suitable for optimizing a broad class of problems of interest to aerospace antennas and related electromagnetics.