DocumentCode :
2878131
Title :
Genetic algorithm (GA) and particle swarm optimization (PSO) in engineering electromagnetics
Author :
Rahmat-Samii, Yahya
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
fYear :
2003
fDate :
1-3 Oct. 2003
Firstpage :
1
Lastpage :
5
Abstract :
Modern antenna designers are constantly challenged to seek for optimum solutions for complex electromagnetic device designs. The temptation has grown because of ever increasing advances in computational power. The standard brute force design techniques are systematically being replaced by the state-of-the-art optimization techniques. The ability of using numerical methods to accurately and efficiently characterizing the relative quality of a particular design has excited the EM engineers to apply stochastic global optimizers. The genetic algorithm (GA) is the most popular of the so-called evolutionary methods in the electromagnetics community. Recently, a new stochastic algorithm called particle swarm optimization (PSO) has been shown to be a valuable addition to the electromagnetic design engineer´s toolbox. In this paper we provide an overview of both techniques and present some representative examples. Most of the material incorporated in this invited plenary session paper is based on the earlier publication work by the author and his students at UCLA.
Keywords :
antennas; computational electromagnetics; electromagnetic devices; genetic algorithms; numerical analysis; stochastic programming; antenna designer; computational power; electromagnetic device design; electromagnetic toolbox; engineering electromagnetic; evolutionary method; genetic algorithm; numerical method; particle swarm optimization; standard brute force design technique; state-of-the-art optimization technique; stochastic algorithm; stochastic global optimizer; Design engineering; Design optimization; Electromagnetic devices; Electromagnetic forces; Genetic algorithms; Genetic engineering; Particle swarm optimization; Power engineering and energy; Power engineering computing; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Electromagnetics and Communications, 2003. ICECom 2003. 17th International Conference on
Print_ISBN :
953-6037-39-4
Type :
conf
DOI :
10.1109/ICECOM.2003.1290941
Filename :
1290941
Link To Document :
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