A Novel Quantum Binary Evolutionary Algorithm for em Applications: BGA-QCO

It is possible to effectively study most of engineering optimization problems suitably rephrased in binary via Evolutionary Algorithms. Even so, the fitness function computation, typically dealing with antenna design, may be very time consuming. Therefore, it is very important to speed up the convergency and to improve the performances of these algorithms, and the introduction of quantum computing seems to open new perspectives, where new approaches have to be considered to exploit the specificity of these instruments. In this paper, a novel quantum version of the binary Genetic Algorithm, bGA, has been introduced, bGA-QCO, and tested on a benchmark function and on a thinned array design.