• DocumentCode
    593278
  • Title

    Study on genetic algorithm and evolutionary programming

  • Author

    Gao Wei

  • Author_Institution
    Wuhan Polytech. Univ., Wuhan, China
  • fYear
    2012
  • fDate
    6-8 Dec. 2012
  • Firstpage
    762
  • Lastpage
    766
  • Abstract
    Genetic algorithm and evolutionary programming are two generally used evolutionary algorithms. Due to the difference of their origin, there are a lot of differences between their biologic bases, algorithm operation and some other operational details. So, the performances of the two algorithms are different. In this paper, these differences are analyzed comprehensively by theory and revealed by simulation experiments. The results show that the performance of evolutionary programming is better than that of genetic algorithm and the evolutionary programming is more suitable for practical applications.
  • Keywords
    evolutionary computation; algorithm operation; biologic bases; evolutionary algorithms; evolutionary programming; genetic algorithm; performance improvement; Biological information theory; Biological system modeling; Biomedical optical imaging; Programming; compairson study; evolutionary algorithm; evolutionary programming; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Distributed and Grid Computing (PDGC), 2012 2nd IEEE International Conference on
  • Conference_Location
    Solan
  • Print_ISBN
    978-1-4673-2922-4
  • Type

    conf

  • DOI
    10.1109/PDGC.2012.6449918
  • Filename
    6449918