Aplicación de PSO y GAs a la síntesis de agrupaciones lineales de antenas
Author
Correa Sanz, Marcos Antonio; Villanueva Baró, Javier; Pérez López, Jesús Ramón

Date
2005-09Derechos
© 2005 URSI España
Publicado en
URSI 2005, XXIV Simposium Nacional de la Unión Científica Internacional de Radio, Santander
Abstract:
Genetic algorithms (GAs) and Particle Swarm Optimization (PSO) are commonly used to solve many optimization and synthesis problems. An important issue facing the user is the selection of their parameters, such as crossover and mutation strategies and rates in GAs, or the population size and boundary conditions in PSO. This paper shows an exhaustive process to obtain those parameters and demonstrates that PSO is more efficient than the real-valued GA when both are applied to linear array synthesis. PSO, with less computational burden and generally fewer lines of code than GAs, turns out to be a more efficent algorithm for the design problem analyzed.
Collections to which it belong
- D12 Congresos [545]