Abstract
Whereas the selection concept of Genetic Algorithms (GAs) and Genetic Programming (GP) is basically realized by the selection of above-average parents for reproduction, Evolution Strategies (ES) use the fitness of newly evolved offspring as the basis for selection (survival of the fittest due to birth surplus). This contribution proposes a generic and enhanced selection model for GAs considering selection aspects of population genetics and ES. Some selected aspects of these enhanced techniques are discussed exemplarily on the basis of standardized benchmark problems.
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Affenzeller, M., Wagner, S., Winkler, S. (2005). GA-Selection Revisited from an ES-Driven Point of View. In: Mira, J., Álvarez, J.R. (eds) Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. IWINAC 2005. Lecture Notes in Computer Science, vol 3562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499305_27
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DOI: https://doi.org/10.1007/11499305_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26319-7
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