Crossover, population dynamics, and convergence in the GAuGE system

Miguel Nicolau; Conor Ryan

doi:10.1007/978-3-540-24854-5_134

Crossover, population dynamics, and convergence in the GAuGE system

Miguel Nicolau, Conor Ryan

University of Limerick

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This paper presents a study of the effectiveness of a recently presented crossover operator for the GAuGE system. This crossover, unlike the traditional crossover employed previously, preserves the association of positions and values which exists in GAuGE genotype strings, and as such is more adequate for problems where the meaning of an allele is dependent on its placement in the phenotype string. Results obtained show that the new operator improves the performance of the GAuGE system on simple binary problems, both when position-sensitive data is manipulated and not.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Kalyanmoy Deb, Riccardo Poli, Owen Holland, Kalyanmoy Banzhaf, Hans-Georg Beyer, Edmund Burke, Paul Darwen, Dipankar Dasgupta, Dario Floreano, James Foster, Mark Harman, Pier Luca Lanzi, Lee Spector, Andrea G. B. Tettamanzi, Dirk Thierens, Andrew M. Tyrrell
Publisher	Springer Verlag
Pages	1414-1425
Number of pages	12
ISBN (Print)	3540223444, 9783540223443
DOIs	https://doi.org/10.1007/978-3-540-24854-5_134
Publication status	Published - 2004

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3102
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-540-24854-5_134

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Nicolau, M., & Ryan, C. (2004). Crossover, population dynamics, and convergence in the GAuGE system. In K. Deb, R. Poli, O. Holland, K. Banzhaf, H.-G. Beyer, E. Burke, P. Darwen, D. Dasgupta, D. Floreano, J. Foster, M. Harman, P. L. Lanzi, L. Spector, A. G. B. Tettamanzi, D. Thierens, & A. M. Tyrrell (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 1414-1425). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3102). Springer Verlag. https://doi.org/10.1007/978-3-540-24854-5_134

Nicolau, Miguel ; Ryan, Conor. / Crossover, population dynamics, and convergence in the GAuGE system. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Kalyanmoy Deb ; Riccardo Poli ; Owen Holland ; Kalyanmoy Banzhaf ; Hans-Georg Beyer ; Edmund Burke ; Paul Darwen ; Dipankar Dasgupta ; Dario Floreano ; James Foster ; Mark Harman ; Pier Luca Lanzi ; Lee Spector ; Andrea G. B. Tettamanzi ; Dirk Thierens ; Andrew M. Tyrrell. Springer Verlag, 2004. pp. 1414-1425 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper presents a study of the effectiveness of a recently presented crossover operator for the GAuGE system. This crossover, unlike the traditional crossover employed previously, preserves the association of positions and values which exists in GAuGE genotype strings, and as such is more adequate for problems where the meaning of an allele is dependent on its placement in the phenotype string. Results obtained show that the new operator improves the performance of the GAuGE system on simple binary problems, both when position-sensitive data is manipulated and not.",

author = "Miguel Nicolau and Conor Ryan",

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Nicolau, M & Ryan, C 2004, Crossover, population dynamics, and convergence in the GAuGE system. in K Deb, R Poli, O Holland, K Banzhaf, H-G Beyer, E Burke, P Darwen, D Dasgupta, D Floreano, J Foster, M Harman, PL Lanzi, L Spector, AGB Tettamanzi, D Thierens & AM Tyrrell (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3102, Springer Verlag, pp. 1414-1425. https://doi.org/10.1007/978-3-540-24854-5_134

Crossover, population dynamics, and convergence in the GAuGE system. / Nicolau, Miguel; Ryan, Conor.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Kalyanmoy Deb; Riccardo Poli; Owen Holland; Kalyanmoy Banzhaf; Hans-Georg Beyer; Edmund Burke; Paul Darwen; Dipankar Dasgupta; Dario Floreano; James Foster; Mark Harman; Pier Luca Lanzi; Lee Spector; Andrea G. B. Tettamanzi; Dirk Thierens; Andrew M. Tyrrell. Springer Verlag, 2004. p. 1414-1425 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3102).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Nicolau M, Ryan C. Crossover, population dynamics, and convergence in the GAuGE system. In Deb K, Poli R, Holland O, Banzhaf K, Beyer HG, Burke E, Darwen P, Dasgupta D, Floreano D, Foster J, Harman M, Lanzi PL, Spector L, Tettamanzi AGB, Thierens D, Tyrrell AM, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 1414-1425. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-24854-5_134

Crossover, population dynamics, and convergence in the GAuGE system

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