• DocumentCode
    3064204
  • Title

    Efficiency of Local Genetic Algorithm in Parallel Processing

  • Author

    Gang, Peng ; Iimura, Ichiro ; Nakatsuru, Takeshi ; Nakayama, Shigeru

  • Author_Institution
    Oita National College of Technology Maki, Oita City, Japan
  • fYear
    2005
  • fDate
    05-08 Dec. 2005
  • Firstpage
    620
  • Lastpage
    623
  • Abstract
    This paper discusses a parallel genetic algorithm (GA) which focuses on the local operator for Traveling salesman problem (TSP). The local operator is a simple GA named as Local Genetic Algorithm (LGA). The LGA is combined to another GA named as Global Genetic Algorithm (GGA). It increases the computational time running a GA as a local operator in another one. To solve this problem, we build a parallel system based on our previous works for running the LGA to speed up the process. The results show that LGA improve the search quality significantly and it is more efficient running LGA with parallel system than single CPU.
  • Keywords
    Traveling Salesman Problem; genetic algorithm (GA); global GA; local GA; object shared space; parallel GA; Cities and towns; Computer science; Concurrent computing; Control engineering; Control engineering computing; Educational institutions; Genetic algorithms; Genetic mutations; Parallel processing; Traveling salesman problems; Traveling Salesman Problem; genetic algorithm (GA); global GA; local GA; object shared space; parallel GA;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. Sixth International Conference on
  • Print_ISBN
    0-7695-2405-2
  • Type

    conf

  • DOI
    10.1109/PDCAT.2005.129
  • Filename
    1578994