Extending the GA-EDA hybrid algorithm to study diversification and intensification in GAs and EDAs

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Abstract

Hybrid metaheuristics have received considerable interest in recent years. Since several years ago, a wide variety of hybrid approaches have been proposed in the literature including the new GA-EDA approach. We have design and implemented an extension to this GA-EDA approach, based on statistical significance tests. This approach had allowed us to make an study of the balance of diversification (exploration) and intensification (exploitation) in Genetic Algorithms and Estimation of Distribution Algorithms. © Springer-Verlag Berlin Heidelberg 2005.

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Robles, V., Peña, J. M., Pérez, M. S., Herrero, P., & Cubo, O. (2005). Extending the GA-EDA hybrid algorithm to study diversification and intensification in GAs and EDAs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3646 LNCS, pp. 339–350). Springer Verlag. https://doi.org/10.1007/11552253_31

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