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.
Meta-PSO techniques for multi-objective optimization of non-uniform planar arrays / M. Mussetta;P. Pirinoli;S. Selleri; R.E. Zich. - STAMPA. - (2009), pp. 1-4. (Intervento presentato al convegno 2009 IEEE Antennas and Propagation Society International Symposium tenutosi a Charleston, NC nel 1-5 June 2009) [10.1109/APS.2009.5171519].
Meta-PSO techniques for multi-objective optimization of non-uniform planar arrays
SELLERI, STEFANO;
2009
Abstract
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.
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
