• DocumentCode
    1869403
  • Title

    The gambler´s ruin problem, genetic algorithms, and the sizing of populations

  • Author

    Harik, Georges ; Cantú-Paz, Erick ; Goldberg, David E. ; Miller, Brad L.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • fYear
    1997
  • fDate
    13-16 Apr 1997
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    The paper presents a model for predicting the convergence quality of genetic algorithms. The model incorporates previous knowledge about decision making in genetic algorithms and the initial supply of building blocks in a novel way. The result is an equation that accurately predicts the quality of the solution found by a GA using a given population size. Adjustments for different selection intensities are considered and computational experiments demonstrate the effectiveness of the model
  • Keywords
    convergence; decision theory; genetic algorithms; probability; GA; building blocks; computational experiments; convergence quality prediction; decision making; gamblers ruin problem; genetic algorithms; population size; population sizing; previous knowledge; selection intensities; Computer science; Convergence; Decision making; Equations; Genetic algorithms; Genetic engineering; Laboratories; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1997., IEEE International Conference on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    0-7803-3949-5
  • Type

    conf

  • DOI
    10.1109/ICEC.1997.592259
  • Filename
    592259
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1869403