• DocumentCode
    1877267
  • Title

    Hybrid Genetic-Ant Optimization Algorithm for continuous functions

  • Author

    Udawant, P. ; Patil, Nahush

  • Author_Institution
    Dept. of Comput. Eng., R.C. Patel Inst. of Technol., Shirpur, India
  • fYear
    2012
  • fDate
    6-8 Dec. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    During the last few years, Evolutionary Computation has its growth to the extent. Its computation approaches such as Genetic Algorithms and Ant Colony Algorithm are used in optimization of the problems. These procedures and computational techniques as a result with their performance are evaluated and compared. The problem area here in this paper we have chosen is continuous functions for the simulation of values. The Hybrid form of Ant Colony Algorithm and Genetic Algorithm obtains better result than their individual implementations.
  • Keywords
    ant colony optimisation; genetic algorithms; ant colony algorithm; computation approaches; computational techniques; continuous functions; evolutionary computation; hybrid genetic-ant optimization algorithm; Ant Colony Algorithm; Continuous Functions; Genetic Algorithm; Mutation and Crossover;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering (NUiCONE), 2012 Nirma University International Conference on
  • Conference_Location
    Ahmedabad
  • Print_ISBN
    978-1-4673-1720-7
  • Type

    conf

  • DOI
    10.1109/NUICONE.2012.6493183
  • Filename
    6493183