• 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