• DocumentCode
    626843
  • Title

    Genetic Algorithm with virus infection for finding approximate solution

  • Author

    Inoue, Takeru ; Uwate, Yoko ; Nishio, Yusuke

  • Author_Institution
    Tokushima Univ., Tokushima, Japan
  • fYear
    2013
  • fDate
    19-23 May 2013
  • Firstpage
    1604
  • Lastpage
    1607
  • Abstract
    Genetic Algorithm (GA) is modeling behavior of evolution in organic and known as one of method to solve Traveling Salesman Problem (TSP). However, GA obtains solution by overlaying generations because of being based on evolution in organic. Thus, it takes a long time to find approximate solution. While, Virus Theory of Evolution (VTE) can evolve by virus infection. VTE characteristic has sharing of information among same generation. If new algorithm is using both these characteristics of GA and VTE, convergence speed would be faster than GA. Thus, this study proposes Genetic Algorithm with Virus Infection (GAVI). GAVI algorithm is Virus Theory of Evolution (VTE) to be based on Genetic Algorithm (GA). We apply GAVI to TSP and confirm that GAVI obtains more effective result than GA.
  • Keywords
    genetic algorithms; travelling salesman problems; GAVI algorithm; TSP; VTE characteristic; approximate solution; convergence speed; evolution modeling behavior; genetic algorithm-virus infection algorithm; traveling salesman problem; virus theory-of-evolution; Approximation algorithms; Cities and towns; Convergence; Error analysis; Genetic algorithms; Genetics; Organisms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
  • Conference_Location
    Beijing
  • ISSN
    0271-4302
  • Print_ISBN
    978-1-4673-5760-9
  • Type

    conf

  • DOI
    10.1109/ISCAS.2013.6572168
  • Filename
    6572168