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Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Author(s): Godley, Paul Michael
Cowie, Julie
Cairns, David
McCall, John
Howie, Catherine
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Title: 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). IEEE World Congress on Computational Intelligence. IEEE Congress on Evolutionary Computation 2008, CEC 2008, Piscataway, NJ, 01.06.2008-06.06.2008. Piscataway, NJ: IEEE (Institute of Electrical and Electronics Engineers), pp. 2532-2537.;
Issue Date: Jun-2008
Series/Report no.: IEEE World Congress on Computational Intelligence
Conference Name: IEEE Congress on Evolutionary Computation 2008, CEC 2008
Conference Dates: 2008-06-01 - 2008-06-06
Conference Location: Hong Kong
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.
Status: AM - Accepted Manuscript
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