• DocumentCode
    2313782
  • Title

    SGA Implementation Using Integer Arrays for Storage of Binary Strings

  • Author

    Kanchan, Pradeep ; D´Souza, Rio

  • Author_Institution
    Dept. of Comput. Sci. & Eng., St.Joseph Eng. Coll., Vamanjoor, India
  • fYear
    2010
  • fDate
    9-11 Feb. 2010
  • Firstpage
    135
  • Lastpage
    136
  • Abstract
    The Simple Genetic Algorithm evaluates a group of binary strings on the basis of their fitness, performs crossover and mutation on them and tries to generate a group having maximum fitness. The usual method used for implementing the SGA is by using character arrays for storage of binary strings. But, this method has some disadvantages. The SGA implementation can be termed a success if the average fitness of the new generation is more than the initial average fitness. In this paper, we plan to implement the SGA using integer arrays for storage of binary strings. Then, we plan to compare the initial average fitness with the final average fitness so that the working of SGA can be verified. We have written the application such that varying population sizes can be given to check the correctness of the SGA algorithm.
  • Keywords
    genetic algorithms; string matching; SGA implementation; binary strings storage; character arrays; initial average fitness; integer arrays; maximum fitness; simple genetic algorithm; Biological cells; Computer science; Educational institutions; Genetic algorithms; Genetic engineering; Genetic mutations; Machine learning; Performance evaluation; Probability; binary string; crossover; fitness function; mutation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Computing (ICMLC), 2010 Second International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4244-6006-9
  • Electronic_ISBN
    978-1-4244-6007-6
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.62
  • Filename
    5460754