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
Link To Document :
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