The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy

Paul M. Godley; David E. Cairns; Julie Cowie; Kevin M. Swingler; John McCall

doi:10.1145/1389095.1389300

The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy

Paul M. Godley, David E. Cairns, Julie Cowie, Kevin M. Swingler, John McCall

NMAHP

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

Abstract

This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike traditional Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the ftness of the parents selected for crossover. This work describes how directed intervention crossover principles are more robust to mutation and lead to significant improvement over UC when applied to cancer chemotherapy treatment scheduling.

Original language	English
Title of host publication	Proceedings of the 10th annual conference on Genetic and evolutionary computation
Editors	Maarten Keijzer
Place of Publication	New York
Publisher	ACM
Pages	1105-1106
Number of pages	2
ISBN (Print)	9781605581309
DOIs	https://doi.org/10.1145/1389095.1389300
Publication status	Published - 30 Nov 2007

Keywords

Optimal Control
Chemotherapy
Crossover
Genetic Algorithms
Genetics Mathematical models
Control theory
Genetics Computer simulation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Documents and Links

10.1145/1389095.1389300

http://hdl.handle.net/1893/1527

Cite this

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title = "The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy",

abstract = "This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike traditional Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the ftness of the parents selected for crossover. This work describes how directed intervention crossover principles are more robust to mutation and lead to significant improvement over UC when applied to cancer chemotherapy treatment scheduling.",

keywords = "Optimal Control, Chemotherapy, Crossover, Genetic Algorithms, Genetics Mathematical models, Control theory, Genetics Computer simulation",

author = "Godley, {Paul M.} and Cairns, {David E.} and Julie Cowie and Swingler, {Kevin M.} and John McCall",

year = "2007",

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language = "English",

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The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy. / Godley, Paul M.; Cairns, David E.; Cowie, Julie; Swingler, Kevin M.; McCall, John.

Proceedings of the 10th annual conference on Genetic and evolutionary computation. ed. / Maarten Keijzer. New York : ACM, 2007. p. 1105-1106.

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

TY - GEN

T1 - The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy

AU - Godley, Paul M.

AU - Cairns, David E.

AU - Cowie, Julie

AU - Swingler, Kevin M.

AU - McCall, John

PY - 2007/11/30

Y1 - 2007/11/30

N2 - This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike traditional Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the ftness of the parents selected for crossover. This work describes how directed intervention crossover principles are more robust to mutation and lead to significant improvement over UC when applied to cancer chemotherapy treatment scheduling.

AB - This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike traditional Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the ftness of the parents selected for crossover. This work describes how directed intervention crossover principles are more robust to mutation and lead to significant improvement over UC when applied to cancer chemotherapy treatment scheduling.

KW - Optimal Control

KW - Chemotherapy

KW - Crossover

KW - Genetic Algorithms

KW - Genetics Mathematical models

KW - Control theory

KW - Genetics Computer simulation

U2 - 10.1145/1389095.1389300

DO - 10.1145/1389095.1389300

M3 - Conference contribution

SN - 9781605581309

SP - 1105

EP - 1106

BT - Proceedings of the 10th annual conference on Genetic and evolutionary computation

A2 - Keijzer, Maarten

PB - ACM

CY - New York

ER -

The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy

Abstract

Keywords

UN SDGs

Documents and Links

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