DocumentCode
589430
Title
Optimization Algorithm of Evolutionary Design of Circuits Based on Genetic Algorithm
Author
Xuejun Song ; Yanli Cui ; Aiting Li
Author_Institution
Coll. of Phys. Sci. & Inf. Eng., Hebei Normal Univ., Shijiazhuang, China
Volume
1
fYear
2012
fDate
28-29 Oct. 2012
Firstpage
336
Lastpage
339
Abstract
For the convergence speed and scale bottlenecks of evolutionary design of circuits, the paper explores a new evolutionary method on the basis of genetic algorithm. Several optimization methods including fitness sharing, exponential weighting, double selection population, "Queen bee" mating, module crossover and optimal solution set are proposed to improve genetic algorithm. the new algorithm improved fitness evaluation method and genetic strategies. the experiment shows that the new evolutionary algorithm accelerates evolution convergence greatly, improves the adaptability effectively and expands the scale of evolved circuit obviously.
Keywords
circuit optimisation; genetic algorithms; network synthesis; circuit evolutionary design; convergence speed; exponential weighting; fitness evaluation method; fitness sharing; genetic algorithm; optimal solution set; optimization algorithm; queen bee mating; Biological cells; Convergence; Evolution (biology); Genetic algorithms; Genetics; Sociology; Statistics; Evolutionary Design of Circuits; Fitness Evaluation; Genetic Algorithm; Optimization Methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4673-2646-9
Type
conf
DOI
10.1109/ISCID.2012.91
Filename
6406989
Link To Document