Abstract
In nature, sexually reproducing organisms do not mate indiscriminately — the choice of mate has an impact upon their offspring’s fitness. The investigation described here shows that, for a wide range of problems in the literature, using sexual selection proved to be a robust method for enhancing genetic algorithm performance. In addition, this investigation provides evidence for which parameters are important for a successful implementation.
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© 1998 Springer-Verlag Wien
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Ratford, M., Tuson, A., Thompson, H. (1998). The Single Chromosome’s Guide to Dating. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_37
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_37
Publisher Name: Springer, Vienna
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