• DocumentCode
    1710437
  • Title

    The performance of the gene expression messy genetic algorithm on real test functions

  • Author

    Kargupta, Hillol

  • Author_Institution
    Comput. Sci. Methods Group, Los Alamos Nat. Lab., NM, USA
  • fYear
    1996
  • Firstpage
    631
  • Lastpage
    636
  • Abstract
    The paper reports the performance of an experimental version of the recently introduced gene expression messy genetic algorithm (GEMGA) (H. Kargupta, 1996) for different classes of real test problems. A more recent version of GEMGA can be found elsewhere. The GEMGA has a strong computational and biological foundation. It emphasizes the role of gene expression in evolution and it searches for relations among genes using transcription like operators. The particular version of GEMGA used in this work is an O(Ak(l+k)) sample complexity algorithm for the class of order-k delineable problems (H. Kargupta, 1995) (problems that can be solved by considering no higher than order-k relations)
  • Keywords
    computational complexity; genetic algorithms; search problems; GEMGA; biological foundation; evolution; gene expression messy genetic algorithm; order-k delineable problems; real test functions; real test problems; sample complexity algorithm; transcription like operators; Biology computing; DNA computing; Evolution (biology); Evolutionary computation; Gene expression; Genetic algorithms; Laboratories; Proteins; Sequences; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
  • Conference_Location
    Nagoya
  • Print_ISBN
    0-7803-2902-3
  • Type

    conf

  • DOI
    10.1109/ICEC.1996.542674
  • Filename
    542674