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A taxonomy for the crossover operator for real-coded genetic algorithms: An experimental study

✍ Scribed by F. Herrera; M. Lozano; A. M. Sánchez

Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
201 KB
Volume
18
Category
Article
ISSN
0884-8173

No coin nor oath required. For personal study only.

✦ Synopsis

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.

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