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Fitness directed intervention crossover approaches applied to bio-scheduling problems

Fitness directed intervention crossover approaches applied to bio-scheduling problems

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

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Authors

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

Research units

Info

Original languageEnglish
Title of host publication2008 IEEE symposium on computational intelligence in bioinformatics and computational biology
Place of publicationPiscataway, N.J.
PublisherIEEE Computer Society
Publication date2008
Pages92-99
Number of pages8
ISBN (Print)9781424417780
StatePublished

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

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.

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