• DocumentCode
    2693186
  • Title

    A new hybrid Self Organizing Migrating Genetic Algorithm for function optimization

  • Author

    Deep, Kusum ; Dipti

  • Author_Institution
    Indian Inst. of Technol., Roorkee
  • fYear
    2007
  • fDate
    25-28 Sept. 2007
  • Firstpage
    2796
  • Lastpage
    2803
  • Abstract
    This paper presents a new self organizing migrating genetic algorithm (SOMGA) for function optimization, which is inspired by the features of self organizing migrating algorithm (SOMA). The uniqueness of this algorithm is that it is hybridization of binary coded GA and real coded SOMA We compare its performance to simple genetic algorithm (GA) and SOMA on 25 test functions. This algorithm is shown to be far more robust than GA and SOMA providing fast convergence across a broad range of parameter settings.
  • Keywords
    genetic algorithms; self-adjusting systems; binary coded genetic algorithm; function optimization; self organizing migrating genetic algorithm; Evolutionary computation; Genetic algorithms; Organizing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1339-3
  • Electronic_ISBN
    978-1-4244-1340-9
  • Type

    conf

  • DOI
    10.1109/CEC.2007.4424825
  • Filename
    4424825
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2693186