Meta-PSO techniques for multi-objective optimization of non-uniform planar arrays

This paper presents the extension of the meta particle swarm optimization (Meta-PSO) evolutionary algorithms to the multi-objective optimization of electromagnetic structures. Particle swarm optimization (PSO) is a global stochastic optimization technique in which the parameter space of the function to be optimized is spanned by particles whose behavior simulates that of a swarm. In the standard PSO the position of each particle is used to compute the value of the function to be optimized. Individual particles are then attracted, stochastically, by both their best past positions and by the global best position of the whole swarm.