On the performance of Genetic Operators the Random Key Representation

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{ryan:2004:eurogp,

• author = "Eoin Ryan and Atif Azad and Conor Ryan",
• title = "On the performance of Genetic Operators the Random Key Representation",
• booktitle = "Genetic Programming 7th European Conference, EuroGP 2004, Proceedings",
• year = "2004",
• editor = "Maarten Keijzer and Una-May O'Reilly and Simon M. Lucas and Ernesto Costa and Terence Soule",
• volume = "3003",
• series = "LNCS",
• pages = "162--173",
• address = "Coimbra, Portugal",
• publisher_address = "Berlin",
• month = "5-7 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-21346-5",
• DOI = "doi:10.1007/978-3-540-24650-3_15",
• abstract = "Many evolutionary systems have been developed that solve various specific scheduling problems. One such permutation based system, which uses a linear GP type Genotype to Phenotype Mapping (GPM), known as the Random Key Genetic Algorithm is investigated. The role standard mutation plays in this representation is analysed formally and is shown to be extremely disruptive. To ensure small fixed sized changes in the phenotype a swap mutation operator is suggested for this representation. An empirical investigation reveals that swap mutation outperforms the standard mutation to solve a hard deceptive problem even without the use of crossover. Swap mutation is also used in conjunction with different crossover operators and significant boost has been observed in the performance especially in the case of headless chicken crossover that produced surprising results.",
• notes = "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in conjunction with EvoCOP2004 and EvoWorkshops2004",

}

Genetic Programming entries for Eoin Ryan R Muhammad Atif Azad Conor Ryan

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