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

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John McCallAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1105 - 1106

https://doi.org/10.1145/1389095.1389300

Published: 12 July 2008 Publication History

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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 fitness 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.

References

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P. M. Godley, D. E. Cairns, and J. Cowie. Directed intervention crossover applied to bio-control scheduling. In IEEE CEC 2007: Proceedings of the IEEE Congress On Evolutionary Computation. IEEE press, 2007.

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[3]

J. McCall, A. Petrovski, and S. Shakya. Evolutionary algorithms for cancer chemotherapy optimization. In G. B. Fogel, D. W. Corne, and Y. Pan, editors, Computational Intelligence in Bioinformatics, chapter 12, pages 265--296. Wiley IEEE Press, 2008.

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A. Petrovski, S. Shakya, and J. McCall. Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms. In GECCO .06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, pages 413--418, New York, NY, USA, 2006. ACM.

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T. Wheldon. Mathematical models in cancer research. IOP Publishing Ltd., Bristol, 1988.

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Index Terms

The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy
1. Computing methodologies
  1. Artificial intelligence
    1. Planning and scheduling

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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Association for Computing Machinery

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Evolution of Appropriate Crossover and Mutation Operators in a Genetic Process

A parameter-less genetic algorithm with customized crossover and mutation operators

An Improved Genetic Algorithm with Average-bound Crossover and Wavelet Mutation Operations

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