A comparative study of linear encoding in Genetic Programming

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

@InProceedings{Suttasupa:2011:ICTKE,

• author = "Yuttana Suttasupa and Suppat Rungraungsilp and Suwat Pinyopan and Pravit Wungchusunti and Prabhas Chongstitvatana",
• title = "A comparative study of linear encoding in Genetic Programming",
• booktitle = "9th International Conference on ICT and Knowledge Engineering (ICT Knowledge Engineering 2011)",
• year = "2012",
• month = "12-13 " # jan,
• pages = "13--17",
• size = "5 pages",
• abstract = "Genetic Programming is a widely used technique to solve many optimisation problems. The original representation of a solution is a tree structure. To improve its search capability there are many proposals for encoding data structure of a solution of Genetic Programming as a linear code. However there are a few work in comparing between these proposals. This work presents a systematic way to compare three popular techniques for linear encoding in Genetic Programming. They are Linear Genetic Programming, Gene Expression Programming and Multi-Expression Programming. Ten problems in Symbolic Expressions are defined and are used as benchmarks to compare the effectiveness of these proposals against the baseline standard Genetic Programming. The metrics of comparison are the Success Rate and the absolute error. The discussion and comparison of the strength and weakness of each method are also presented.",
• keywords = "genetic algorithms, genetic programming, Gene Expression Programming, Multi-Expression Programming, absolute error, data structure encoding, linear code, linear encoding, linear genetic programming, optimisation problem, success rate, symbolic expressions, tree structure, tree data structures",
• DOI = "doi:10.1109/ICTKE.2012.6152392",
• notes = "Also known as \cite{6152392}",

}

Genetic Programming entries for Yuttana Suttasupa Suppat Rungraungsilp Suwat Pinyopan Pravit Wungchusunti Prabhas Chongstitvatana

Citations