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Differential Evolution (DE) stochastic algorithms for global optimization of problems with and without constraints. The aim is to curate a collection of its state-of-the-art variants that (1) do not sacrifice simplicity of design, (2) are essentially tuning-free, and (3) can be efficiently implemented directly in the R language. Currently, it only provides an implementation of the 'jDE' algorithm by Brest et al. (2006) <doi:10.1109/TEVC.2006.872133>. WWW: https://cran.r-project.org/web/packages/DEoptimR/
9 lines
511 B
Text
9 lines
511 B
Text
Differential Evolution (DE) stochastic algorithms for global
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optimization of problems with and without constraints. The aim is
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to curate a collection of its state-of-the-art variants that (1)
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do not sacrifice simplicity of design, (2) are essentially tuning-free,
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and (3) can be efficiently implemented directly in the R language.
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Currently, it only provides an implementation of the 'jDE' algorithm
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by Brest et al. (2006) <doi:10.1109/TEVC.2006.872133>.
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WWW: https://cran.r-project.org/web/packages/DEoptimR/
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