Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches

Paul Godley; Julie Cowie; David Cairns; John McCall; Catherine Howie

doi:10.1109/CEC.2008.4631138

Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches

Paul Godley, Julie Cowie, David Cairns, John McCall, Catherine Howie

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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.

Original language	English
Title of host publication	IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence)
Place of Publication	New York
Publisher	IEEE Computer Society
Pages	2532-2537
Number of pages	6
ISBN (Print)	9781424418220
DOIs	https://doi.org/10.1109/CEC.2008.4631138
Publication status	Published - 2008
Event	2008 IEEE Congress on Evolutionary Computation - Hong Kong, China Duration: 1 Jun 2008 → 6 Jun 2008 http://www2.mae.cuhk.edu.hk/~wcci2008/

Conference

Conference	2008 IEEE Congress on Evolutionary Computation
Abbreviated title	CEC 2008
Country/Territory	China
City	Hong Kong
Period	1/06/08 → 6/06/08
Other	Held as part of WCCI 2008 - the joint event of 2008 International Joint Conference on Neural Networks (IJCNN 2008), 2008 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2008), and 2008 IEEE Congress on Evolutionary Computation (CEC 2008).
Internet address	http://www2.mae.cuhk.edu.hk/~wcci2008/

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10.1109/CEC.2008.4631138

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@inproceedings{3db45cf02751479da6eec85c8be941d5,

title = "Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches",

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.",

author = "Paul Godley and Julie Cowie and David Cairns and John McCall and Catherine Howie",

year = "2008",

doi = "10.1109/CEC.2008.4631138",

language = "English",

isbn = "9781424418220",

pages = "2532--2537",

booktitle = "IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence)",

publisher = "IEEE Computer Society",

note = "2008 IEEE Congress on Evolutionary Computation, CEC 2008 ; Conference date: 01-06-2008 Through 06-06-2008",

url = "http://www2.mae.cuhk.edu.hk/~wcci2008/",

}

Godley, P, 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 Computer Society, New York, pp. 2532-2537, 2008 IEEE Congress on Evolutionary Computation, Hong Kong, China, 1/06/08. https://doi.org/10.1109/CEC.2008.4631138

Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches. / Godley, Paul; Cowie, Julie; Cairns, David et al.
IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). New York: IEEE Computer Society, 2008. p. 2532-2537.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches

AU - Godley, Paul

AU - Cowie, Julie

AU - Cairns, David

AU - McCall, John

AU - Howie, Catherine

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

U2 - 10.1109/CEC.2008.4631138

DO - 10.1109/CEC.2008.4631138

M3 - Conference contribution

SN - 9781424418220

SP - 2532

EP - 2537

BT - IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence)

PB - IEEE Computer Society

CY - New York

T2 - 2008 IEEE Congress on Evolutionary Computation

Y2 - 1 June 2008 through 6 June 2008

ER -

Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches

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