Fitness directed intervention crossover approaches applied to bio-scheduling problems

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

Fitness directed intervention crossover approaches applied to bio-scheduling problems

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

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

Abstract

This paper discusses the effects of using directed intervention crossover approaches with Genetic Algorithms (GA) and demonstrates their application to scheduling of bio-control agents and cancer chemotherapy treatments. Unlike traditional approaches such as Single Point Crossover (SPC) or Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work shows that a fitness directed intervention crossover approach leads to significant improvements over SPC and UC when applied to the two different scheduling problems.

Original language	English
Title of host publication	2008 IEEE symposium on computational intelligence in bioinformatics and computational biology
Place of Publication	Piscataway, N.J.
Publisher	IEEE Computer Society
Pages	92-99
Number of pages	8
ISBN (Print)	9781424417780
Publication status	Published - 2008
Event	2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology - Sun Valley, Idaho, United States Duration: 15 Sept 2008 → 17 Sept 2008

Conference

Conference	2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
Abbreviated title	IEEE CIBCB
Country/Territory	United States
City	Sun Valley, Idaho
Period	15/09/08 → 17/09/08

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

Cite this

@inproceedings{0ef68f42c2214d29afaefe2287892c04,

title = "Fitness directed intervention crossover approaches applied to bio-scheduling problems",

abstract = "This paper discusses the effects of using directed intervention crossover approaches with Genetic Algorithms (GA) and demonstrates their application to scheduling of bio-control agents and cancer chemotherapy treatments. Unlike traditional approaches such as Single Point Crossover (SPC) or Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work shows that a fitness directed intervention crossover approach leads to significant improvements over SPC and UC when applied to the two different scheduling problems.",

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

year = "2008",

language = "English",

isbn = "9781424417780",

pages = "92--99",

booktitle = "2008 IEEE symposium on computational intelligence in bioinformatics and computational biology",

publisher = "IEEE Computer Society",

note = "2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, IEEE CIBCB ; Conference date: 15-09-2008 Through 17-09-2008",

}

Godley, PM, Cairns, DE, Cowie, J & McCall, J 2008, Fitness directed intervention crossover approaches applied to bio-scheduling problems. in 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. IEEE Computer Society, Piscataway, N.J., pp. 92-99, 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, Sun Valley, Idaho, United States, 15/09/08.

Fitness directed intervention crossover approaches applied to bio-scheduling problems. / Godley, Paul M.; Cairns, David E.; Cowie, Julie et al.
2008 IEEE symposium on computational intelligence in bioinformatics and computational biology. Piscataway, N.J.: IEEE Computer Society, 2008. p. 92-99.

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

TY - GEN

T1 - Fitness directed intervention crossover approaches applied to bio-scheduling problems

AU - Godley, Paul M.

AU - Cairns, David E.

AU - Cowie, Julie

AU - McCall, John

PY - 2008

Y1 - 2008

N2 - This paper discusses the effects of using directed intervention crossover approaches with Genetic Algorithms (GA) and demonstrates their application to scheduling of bio-control agents and cancer chemotherapy treatments. Unlike traditional approaches such as Single Point Crossover (SPC) or Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work shows that a fitness directed intervention crossover approach leads to significant improvements over SPC and UC when applied to the two different scheduling problems.

AB - This paper discusses the effects of using directed intervention crossover approaches with Genetic Algorithms (GA) and demonstrates their application to scheduling of bio-control agents and cancer chemotherapy treatments. Unlike traditional approaches such as Single Point Crossover (SPC) or Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work shows that a fitness directed intervention crossover approach leads to significant improvements over SPC and UC when applied to the two different scheduling problems.

M3 - Conference contribution

SN - 9781424417780

SP - 92

EP - 99

BT - 2008 IEEE symposium on computational intelligence in bioinformatics and computational biology

PB - IEEE Computer Society

CY - Piscataway, N.J.

T2 - 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

Y2 - 15 September 2008 through 17 September 2008

ER -

Fitness directed intervention crossover approaches applied to bio-scheduling problems

Abstract

Conference

UN SDGs

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