%0 Journal Article 
%A Domínguez Tortajada, Elsa
%A Díaz Morcillo, Alejandro Benedicto
%A Monzó Cabrera, Juan
%A Sánchez Hernández, David Agapito
%T Aplicación de algoritmos genéticos en el diseño de cavidades multialimentadas
%D 2003
%U http://hdl.handle.net/10317/1517
%X Genetic Algorithms are a general purpose
optimization technique that in the last years have begun to be
applied in electromagnetic applications design. In this article,
the study of microwave cavities feeding from two feasible
designs to optimize is presented: feeding by means of
rectangular waveguides and by means of slotted
waveguides.The pursued goal is optimizing and obtaining a
series of design parameters such as the position, orientation and
dimension of the waveguides and slots in the microwave heating
system, in order to maximize the system adaptation. A
combination of these parameters constitutes an individual,
which is evaluated by means of the commercial software
Microwave Studio (CST). The simulation result are the
scattering parameters associated to the individual. The
population determines the number of individuals that conform
each generation. From the initial population, operations of
selection, mutation and recombination are performed, creating
new generations that replace the formers. The best individuals,
in general, have greater possibilities to survive in the next
generation as well as to perform a crossover with other
individuals. That is the way in which the genetic algorithm
searchs for the optimal solution, that is, the best adaptation.The
results show that the solution depends on the number of the
design parameters, on the individuals that constitute the initial
population, and they also display the random component
characteristic of this kind of algorithms.
%K Teoría de la Señal y las Comunicaciones
%K Cavidad multialimentada
%K Calentamiento por microondas
%K Guía de onda
%K MATLAB
%K Tecnica de optimización
%K Cavity multi-fed
%K Microwave heating
%K Waveguide
%K Optimization technique
%K Algoritmos genéticos (AG)
%K Genetic Algorithm (GA)
%~ GOEDOC, SUB GOETTINGEN