A robust real-coded genetic algorithm using an ensemble of crossover operators

Authors:
Jeonghwan Gwak;Moongu Jeon
Affiliations:
Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea;Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

Citing 3
Cited 0

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Abstract

Although a lot of crossover operators have been developed for genetic algorithms (GAs), there is not much research on combining different crossover operators to form robust real-coded GAs. In this work, we propose an ensemble of crossover operators which is realized by two different parallel populations. The effectiveness of the proposed method is evaluated for traditional 6 benchmark functions. Results demonstrated that the proposed method has good generalization performance.