Comparison of evolutionary algorithms for LPDA antenna optimization

A novel approach to broadband log-periodic antenna design is presented, where some of the
most powerful evolutionary algorithms (EAs) are applied and compared for the optimal design of
wire log-periodic dipole arrays (LPDA) using NEC (Numerical Electromagnetics Code). The
target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, Front
to Rear ratio (F/R) and SWR (Standing Wave Ratio). The parameters of the LPDA optimized are
the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The
evolutionary algorithms compared are the: Differential Evolution (DE), Particle Swarm (PSO),
Taguchi, Invasive Weed (IWO) and Adaptive Invasive Weed Optimization (ADIWO). Superior
performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.