Research output

Conference Paper (in Formal Publication) ()

Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches

Citation
Godley PM, Cowie J, Cairns D, McCall J & Howie C (2008) Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches In: IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence), Piscataway, NJ: IEEE (Institute of Electrical and Electronics Engineers). IEEE Congress on Evolutionary Computation 2008, CEC 2008, 1.6.2008 - 6.6.2008, Hong Kong, pp. 2532-2537.

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
Genetic Algorithm; Chemotherapy; Crossover; Optimal Control

StatusPublished
AuthorsGodley Paul Michael, Cowie Julie, Cairns David, McCall John, Howie Catherine
Title of seriesIEEE World Congress on Computational Intelligence
Publication date06/2008
URLhttp://ieeexplore.ieee.org/servlet/opac?punumber=4625778
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of publicationPiscataway, NJ
ISBN 978-1-4244-1822-0
LanguageEnglish
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