Abstract
Genetic algorithms are biological inspired search procedures that have been used to solve different hard problems. They are based on the neo-Darwinian ideas of natural selection and reproduction. Since Holland proposals back in 1975, two main genetic operators, crossover and mutation, have been explored with success. Nevertheless, in nature there exist much more mechanisms for genetic recombination based in phenomena like gene insertion, duplication or movement. The goal of this paper is to study one of these mechanism, called transposition. Transposition is a context-sensitive operator that promotes the movement intra or inter chromosomes. In this preliminary work we empirically study the performance of the genetic algorithm where the traditional crossover operator was substituted by transposition. The results are very promising but must be confirmed by a more extensive empirical study and the correspondent theoretical justification.
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© 1999 Springer-Verlag Wien
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Simões, A., Costa, E. (1999). Transposition: A Biological-Inspired Mechanism to Use with Genetic Algorithms. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6384-9_31
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DOI: https://doi.org/10.1007/978-3-7091-6384-9_31
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83364-3
Online ISBN: 978-3-7091-6384-9
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