• DocumentCode
    3394444
  • Title

    Fitness directed intervention crossover approaches applied to bio-scheduling problems

  • Author

    Godley, Paul M. ; Cairns, David E. ; Cowie, Julie ; McCall, John

  • Author_Institution
    Dept. of Comput. Sci. & Math., Univ. of Stirling, Stirling
  • fYear
    2008
  • fDate
    15-17 Sept. 2008
  • Firstpage
    120
  • Lastpage
    127
  • Abstract
    This paper discusses the effects of using directed intervention crossover approaches with Genetic Algorithms (GA) and demonstrates their application to scheduling of bio-control agents and cancer chemotherapy treatments. Unlike traditional approaches such as Single Point Crossover (SPC) or Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work shows that a fitness directed intervention crossover approach leads to significant improvements over SPC and UC when applied to the two different scheduling problems.
  • Keywords
    biology computing; cancer; genetic algorithms; genetics; patient treatment; bio-control agents; bio-scheduling problems; cancer chemotherapy; fitness directed intervention crossover approaches; genetic algorithms; single point crossover; Algorithm design and analysis; Biological cells; Biological control systems; Cancer; Crops; Drugs; Encoding; Equations; Protection; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology, 2008. CIBCB '08. IEEE Symposium on
  • Conference_Location
    Sun Valley, ID
  • Print_ISBN
    978-1-4244-1778-0
  • Electronic_ISBN
    978-1-4244-1779-7
  • Type

    conf

  • DOI
    10.1109/CIBCB.2008.4675768
  • Filename
    4675768