Abstract
| 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 | |
| Publication status | Published - 30 Nov 2007 |
Fingerprint
Keywords
- Optimal Control
- Chemotherapy
- Crossover
- Genetic Algorithms
- Genetics Mathematical models
- Control theory
- Genetics Computer simulation
Cite this
}
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 -