Genetic algorithm with artificial neural networks as its fitness function to design rectangular microstrip antenna on thick substrate

Over the years, genetic algorithms (GAs) have been applied in many applications. But the lack of a proper fitness function has been a hindrance to its widespread application in many cases. In this paper, a novel technique of using artificial neural networks (ANNs) as the fitness function of a genetic algorithm in order to calculate the design parameters of a thick substrate rectangular microstrip antenna is presented. A multilayer feed-forward neural network is used as the fitness function in a binary-coded genetic algorithm. The results obtained using this method are found to be closer to the experimental value, as compared to previous results obtained using the curve-fitting method. To validate this, the results are compared with the experimental values for five fabricated antennas. The results are in very good agreement with the experimental findings. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 144–146, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20570