Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/2437
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
Contact Email: dec@cs.stir.ac.uk
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, 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
Issue Date: Jun-2008
Date Deposited: 11-Oct-2010
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
Rights: Copyright IEEE; ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. http://www.ieee.org/publications_standards/publications/rights/rights_policies.html; The publisher has not responded to our queries therefore this work cannot be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author; you can only request a copy if you wish to use this work for your own research or private study.
URL: http://ieeexplore.ieee.org/servlet/opac?punumber=4625778
Licence URL(s): http://www.rioxx.net/licenses/under-embargo-all-rights-reserved

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