Conference Paper (published)
Details
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). IEEE World Congress on Computational Intelligence. IEEE Congress on Evolutionary Computation 2008, CEC 2008, Hong Kong, 01.06.2008-06.06.2008. Piscataway, NJ: IEEE (Institute of Electrical and Electronics Engineers), pp. 2532-2537. http://ieeexplore.ieee.org/servlet/opac?punumber=4625778; https://doi.org/10.1109/CEC.2008.4631138
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 ?tness of the parents selected for crossover. Our results indicate that these approaches lead to signi?cant improvements over UC when applied to cancer chemotherapy scheduling.
Keywords
Genetic Algorithm; Chemotherapy; Crossover; Optimal Control
Status | Published |
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Title of series | IEEE World Congress on Computational Intelligence |
Publication date | 30/06/2008 |
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Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
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Place of publication | Piscataway, NJ |
ISBN | 978-1-4244-1822-0 |
Conference | IEEE Congress on Evolutionary Computation 2008, CEC 2008 |
Conference location | Hong Kong |
Dates | – |
People (1)
Lecturer, Computing Science