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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.

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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: Famili, A.F., Kok, J.N., Peña, J.M., Siebes, A., Feelders, A. (eds) Advances in Intelligent Data Analysis VI. IDA 2005. Lecture Notes in Computer Science, vol 3646. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552253_31

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  • DOI: https://doi.org/10.1007/11552253_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28795-7

  • Online ISBN: 978-3-540-31926-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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