Title :
Particle swarm optimization in electromagnetics
Author :
Robinson, Jacob ; Rahmat-Samii, Yahya
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Los Angeles, CA, USA
Abstract :
The particle swarm optimization (PSO), new to the electromagnetics community, is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms. This paper introduces a conceptual overview and detailed explanation of the PSO algorithm, as well as how it can be used for electromagnetic optimizations. This paper also presents several results illustrating the swarm behavior in a PSO algorithm developed by the authors at UCLA specifically for engineering optimizations (UCLA-PSO). Also discussed is recent progress in the development of the PSO and the special considerations needed for engineering implementation including suggestions for the selection of parameter values. Additionally, a study of boundary conditions is presented indicating the invisible wall technique outperforms absorbing and reflecting wall techniques. These concepts are then integrated into a representative example of optimization of a profiled corrugated horn antenna.
Keywords :
antenna theory; electromagnetism; evolutionary computation; genetic algorithms; horn antennas; UCLA; antenna design; corrugated horn antenna; electromagnetics; genetic algorithm; invisible wall technique; particle swarm optimization; stochastic evolutionary computation technique; Algorithm design and analysis; Boundary conditions; Electromagnetics; Evolutionary computation; Genetic algorithms; Horn antennas; Jacobian matrices; Particle swarm optimization; Robustness; Stochastic processes;
Journal_Title :
Antennas and Propagation, IEEE Transactions on
DOI :
10.1109/TAP.2004.823969