Abstract
Turbo code interleaver optimization is a NP-hard combinatorial optimization problem attractive for its complexity and variety of real world applications. In this paper, we investigate the usage and performance of recent variant of genetic algorithms, higher level chromosome genetic algorithms, on the turbo code optimization task. The problem as well as higher level chromosome genetic algorithms, that can be use for combinatorial optimization problems in general, is introduced and experimentally evaluated.
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Snášel, V., Platoš, J., Krömer, P., Ouddane, N. (2009). Genetic Algorithms for the Use in Combinatorial Problems. In: Abraham, A., Hassanien, AE., Siarry, P., Engelbrecht, A. (eds) Foundations of Computational Intelligence Volume 3. Studies in Computational Intelligence, vol 203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01085-9_1
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DOI: https://doi.org/10.1007/978-3-642-01085-9_1
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