Fitness directed intervention crossover approaches applied to bio-scheduling problems

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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    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.

    Original languageEnglish
    Title of host publication2008 IEEE symposium on computational intelligence in bioinformatics and computational biology
    Place of PublicationPiscataway, N.J.
    PublisherIEEE Computer Society
    Pages92-99
    Number of pages8
    ISBN (Print)9781424417780
    Publication statusPublished - 2008
    Event2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology - Sun Valley, Idaho, United States
    Duration: 15 Sep 200817 Sep 2008

    Conference

    Conference2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
    Abbreviated titleIEEE CIBCB
    CountryUnited States
    CitySun Valley, Idaho
    Period15/09/0817/09/08

    Cite this

    Godley, P. M., Cairns, D. E., Cowie, J., & McCall, J. (2008). Fitness directed intervention crossover approaches applied to bio-scheduling problems. In 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology (pp. 92-99). Piscataway, N.J.: IEEE Computer Society.
    Godley, Paul M. ; Cairns, David E. ; Cowie, Julie ; McCall, John. / Fitness directed intervention crossover approaches applied to bio-scheduling problems. 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. Piscataway, N.J. : IEEE Computer Society, 2008. pp. 92-99
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    title = "Fitness directed intervention crossover approaches applied to bio-scheduling problems",
    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.",
    author = "Godley, {Paul M.} and Cairns, {David E.} and Julie Cowie and John McCall",
    year = "2008",
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    Godley, PM, Cairns, DE, Cowie, J & McCall, J 2008, Fitness directed intervention crossover approaches applied to bio-scheduling problems. in 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. IEEE Computer Society, Piscataway, N.J., pp. 92-99, 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, Sun Valley, Idaho, United States, 15/09/08.

    Fitness directed intervention crossover approaches applied to bio-scheduling problems. / Godley, Paul M.; Cairns, David E.; Cowie, Julie; McCall, John.

    2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. Piscataway, N.J. : IEEE Computer Society, 2008. p. 92-99.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    AU - Cowie, Julie

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    N2 - 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.

    AB - 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.

    M3 - Conference contribution

    SN - 9781424417780

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    EP - 99

    BT - 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology

    PB - IEEE Computer Society

    CY - Piscataway, N.J.

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    Godley PM, Cairns DE, Cowie J, McCall J. Fitness directed intervention crossover approaches applied to bio-scheduling problems. In 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. Piscataway, N.J.: IEEE Computer Society. 2008. p. 92-99