A New Crossover Operator in GP for Object Classification

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@TechReport{vuw-CS-TR-06-2,

• author = "Mengjie Zhang and Xiaoying Gao and Weijun Lou",
• title = "A New Crossover Operator in GP for Object Classification",
• institution = "Computer Science, Victoria University of Wellington",
• year = "2006",
• number = "CS-TR-06-2",
• address = "New Zealand",
• month = jan,
• keywords = "genetic algorithms, genetic programming, Crossover points, looseness controlled crossover, hybrid search",
• URL = "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-06-2.abs.html",
• URL = "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS-TR-06-2.pdf",
• abstract = "instead of randomly choosing the crossover points as in the standard crossover operator, we use a measure called looseness to guide the selection of crossover points. Rather than using the genetic beam search only, this approach uses a hybrid beam-hill climbing search scheme in the evolutionary process. This approach is examined and compared with the standard crossover operator and the headless chicken crossover method on a sequence of object classification problems. The results suggest that this approach outperforms both the headless chicken crossover and the standard crossover on all of these problems.",
• size = "17 pages",

}

Genetic Programming entries for Mengjie Zhang Xiaoying (Sharon) Gao Weijun (Norman) Lou

Citations