@misc{10481/64963,
year = {2003},
url = {http://hdl.handle.net/10481/64963},
abstract = {The main real-coded genetic algorithm (RCGA) research effort has been spent on developing
efficient crossover operators. This study presents a taxonomy for this operator that groups its
instances in different categories according to the way they generate the genes of the offspring
from the genes of the parents. The empirical study of representative crossovers of all the
categories reveals concrete features that allow the crossover operator to have a positive influence
on RCGA performance. They may be useful to design more effective crossover models.},
publisher = {WILEY},
title = {A Taxonomy for the Crossover Operator for Real-Coded Genetic Algorithms: An Experimental Study},
doi = {10.1002/int.10091},
author = {Herrera Triguero, Francisco and Lozano Márquez, Manuel},
}