DocumentCode :
2915350
Title :
Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches
Author :
Godley, Paul ; Cowie, Julie ; Cairns, David ; McCall, John ; Howie, Catherine
Author_Institution :
Dept. of Comput. Sci. & Math., Stirling Univ., Stirling
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
2532
Lastpage :
2537
Abstract :
This paper describes two directed intervention crossover approaches that are applied to the problem of deriving optimal cancer chemotherapy treatment schedules. Unlike traditional uniform crossover (UC), both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approaches actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Our results indicate that these approaches lead to significant improvements over UC when applied to cancer chemotherapy scheduling.
Keywords :
cancer; optimisation; radiation therapy; scheduling; stochastic processes; calculated expanding bin method; cancer chemotherapy schedule optimisation; chemotherapy treatment schedules; directed intervention crossover approaches; targeted intervention with stochastic selection; uniform crossover; Cancer; Drugs; Evolutionary computation; Mathematical model; Medical treatment; Protection; Scheduling algorithm; Stochastic processes; Testing; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4631138
Filename :
4631138
Link To Document :
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