An improved quantum genetic algorithm for reconfigurable antenna optimization

A practical reconfigurable antenna (RA), usually equipped with multiple switches, has a high real-time requirement for the optimization algorithm. In this paper, an improved quantum genetic algorithm (IQGA) is proposed to deal with the optimization problem of the RA The algorithm codes the chromosome with probability amplitudes represented by sine and cosine functions, and uses an adaptive strategy of the rotation angle to update the population. Then the mutation operation is considered in this improved quantum genetic algorithm. The experimental results on the optimization of a 39-switch RA show the IQGA has better comprehensive performance than the traditional genetic algorithm (QA) and standard quantum genetic algorithm (QGA) in terms of the solution quality and convergence speed.