- author = "Brian W. Goldman and Daniel R. Tauritz",
- title = "Self-configuring crossover",
- booktitle = "GECCO 2011 1st workshop on evolutionary computation for designing generic algorithms",
- year = "2011",
- editor = "Gisele L. Pappa and Alex A. Freitas and Jerry Swan and John Woodward",
- isbn13 = "978-1-4503-0690-4",
- keywords = "genetic algorithms, genetic programming",
- pages = "575--582",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
DOI = "
doi:10.1145/2001858.2002051",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
-
abstract = "Crossover is a core genetic operator in many
evolutionary algorithms (EAs). The performance of such
EAs on a given problem is dependent on properly
configuring crossover. A small set of common crossover
operators is used in the vast majority of EAs,
typically fixed for the entire evolutionary run.
Selecting which crossover operator to use and tuning
its associated parameters to obtain acceptable
performance on a specific problem often is a time
consuming manual process. Even then a custom crossover
operator may be required to achieve optimal
performance. Finally, the best crossover configuration
may be dependent on the state of the evolutionary
run.
This paper introduces the Self-Configuring Crossover operator encoded with linear genetic programming which addresses these shortcomings while relieving the user from the burden of crossover configuration. To demonstrate its general applicability, the novel crossover operator was applied without any problem specific tuning. Results are presented showing it to outperform the traditional crossover operators arithmetic crossover, uniform crossover, and n-point crossover on the Rosenbrock, Rastrigin, Offset Rastrigin, DTrap, and NK Landscapes benchmark problems.",
-
notes = "Also known as \cite{2002051} Distributed on CD-ROM at
GECCO-2011.
ACM Order Number 910112.",
