Optimizing backscattering from arrays of perfectly conducting strips

Eight different numerical optimization algorithms tackled the problem of finding the best spacings for an array of perfectly conducting strips in order to get desirable backscattering characteristics. Local optimizers worked well when the problem was relatively simple and had few parameters. As the complexity of the problem increased, the genetic algorithm proved a better approach. In general, a hybrid genetic algorithm (GA) worked best, because it combined the power of the local search with a global search. This paper presents optimized results that were averaged over twenty independent runs, and discusses the pros and cons of the various approaches.