- author = "David R. White and Simon Poulding",
- title = "A Rigorous Evaluation of Crossover and Mutation in Genetic Programming",
- booktitle = "Proceedings of the 12th European Conference on Genetic Programming, EuroGP 2009",
- year = "2009",
- editor = "Leonardo Vanneschi and Steven Gustafson and Alberto Moraglio and Ivanoe {De Falco} and Marc Ebner",
- volume = "5481",
- series = "LNCS",
- pages = "220--231",
- address = "Tuebingen",
- month = apr # " 15-17",
- organisation = "EvoStar",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-642-01180-1",
-
DOI = "
doi:10.1007/978-3-642-01181-8_19",
-
URL = "
http://results.ref.ac.uk/Submissions/Output/1867870",
- size = "12 pages",
- abstract = "The role of crossover and mutation in Genetic Programming (GP) has been the subject of much debate since the emergence of the field. In this paper, we contribute new empirical evidence to this argument using a rigorous and principled experimental method applied to six problems common in the GP literature. The approach tunes the algorithm parameters to enable a fair and objective comparison of two different GP algorithms, the first using a combination of crossover and reproduction, and secondly using a combination of mutation and reproduction. We find that crossover does not significantly outperform mutation on most of the problems examined. In addition, we demonstrate that the use of a straightforward Design of Experiments methodology is effective at tuning GP algorithm parameters.",
-
notes = "DOE, {"}millions of runs{"}, ECJ, factorial design.
Vargha-Delaney A statistic. DoE better than response
surface methodology and central composite design.
Sebase.
Part of \cite{conf/eurogp/2009} EuroGP'2009 held in conjunction with EvoCOP2009, EvoBIO2009 and EvoWorkshops2009",
-
uk_research_excellence_2014 = "This was one of the first papers in GP
to employ highly rigorous empirical method, as well as
directly addressing a controversial topic (see Spector
and Luke's earlier works) using this approach.
It was the first to consider response surface modelling, scientific significance, and apply the Vargha-Delaney measure to GP performance.
The paper was short-listed for a best paper award at EuroGP, the premier annual conference on Genetic Programming.",
