DocumentCode
392010
Title
Speeding convergence of genetic algorithms for inverse scattering problems
Author
Misaka, H.
fYear
2002
fDate
17-19 Aug. 2002
Firstpage
414
Lastpage
417
Abstract
As a global optimization method, genetic algorithm (GA) is very convenient for continuous and discrete optimizations, especially for inverse scattering problems, and many remarkable results have been obtained. One of the problems of GA is how to achieve the evolution toward the global minimum efficiently. This paper introduces the techniques of mutating genes and seeding population to speed GA convergence.
Keywords
convergence; electromagnetic wave scattering; genetic algorithms; inverse problems; GA convergence; continuous optimizations; convergence; discrete optimizations; gene mutation; genetic algorithms; global minimum; global optimization method; inverse scattering problems; population seeding; Biological cells; Convergence; Cost function; Evolution (biology); Flowcharts; Genetic algorithms; Genetic mutations; Inverse problems; Optimization methods; Space exploration;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave and Millimeter Wave Technology, 2002. Proceedings. ICMMT 2002. 2002 3rd International Conference on
Print_ISBN
0-7803-7486-X
Type
conf
DOI
10.1109/ICMMT.2002.1187724
Filename
1187724
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