• DocumentCode
    2913625
  • Title

    Improving the performance of LZWGA by using a new mutation method

  • Author

    Numnark, Somrak ; Suwannik, Worasait

  • Author_Institution
    Fac. of Sci., Kasetsart Univ., Bangkok
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    1862
  • Lastpage
    1865
  • Abstract
    LZW encoding in Genetic Algorithm (LZWGA) encodes a chromosome in a format that can be decompressed by Lempel-Ziv-Welch (LZW) algorithm. This encoding reduces the size of the chromosome and enabled the algorithm to solve a very large problem. This paper proposes a novel mutation in LZWGA. The result shows that the new method can solve OneMax and Trap problem 46.3% faster. Moreover, this method can reduce the size of the compressed chromosome by 54.8%.
  • Keywords
    encoding; genetic algorithms; Lempel-Ziv-Welch algorithm; Lempel-Ziv-Welch encoding; compressed chromosome; genetic algorithm; mutation method; Algorithm design and analysis; Compression algorithms; Data compression; Data structures; Dictionaries; Evolutionary computation; Genetic mutations; Heuristic algorithms; Resists; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631042
  • Filename
    4631042