Title :
Speeding convergence of genetic algorithms for inverse scattering problems
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;
Conference_Titel :
Microwave and Millimeter Wave Technology, 2002. Proceedings. ICMMT 2002. 2002 3rd International Conference on
Print_ISBN :
0-7803-7486-X
DOI :
10.1109/ICMMT.2002.1187724
