Military Antenna Design Using Simple and Competent Genetic Algorithms

Over the past decade, the Air Force Research Laboratory (AFRL) antenna Technology Branch at Hanscom AFB has employed the simple genetic algorithm (SGA) as an optimization tool for a wide variety of antenna applications. Over roughly the same period, researchers at the Illinois Genetic Algorithm Laboratory (IlliGAL) at the University of Illinois at Urbana-Champaign have developed GA design theory and advanced GA techniques called competent genetic algorithms that solve hard problems quickly, reliably, and accurately. Recently, under the guidance and direction of the Air Force Office of Scientific Research (AFOSR), the two laboratories have formed a collaboration, the common goal of which is to apply simple, competent, and hybrid GA techniques to challenging antenna problems. This paper is composed of two parts. The first part of this paper summarizes previous research conducted by AFRL at Hanscom for which SGAs were implemented to obtain acceptable solutions to several antenna problems. The second part of this paper starts by briefly reviewing the design theory and design principles necessary for the invention and implementation of fast, scalable genetic algorithms. A particular procedure, the hierarchical Bayesian optimization algorithm (hBOA) is then briefly outlined, and the remainder of the paper describes collaborative efforts of AFRL and IlliGAL to solve more difficult antenna problems.Air Force Research Lab Hanscom AFB MA Sensors Directorate is the author of 'Military Antenna Design Using Simple and Competent Genetic Algorithms', published 2004 under ISBN 9781423521952 and ISBN 1423521951.