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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>.

Type Size Name Uploaded Downloads Labels
conda 44.7 kB | osx-64/r-deoptimr-1.0_8-r351hf348343_0.tar.bz2  6 years and 2 months ago 7 main
conda 45.0 kB | osx-64/r-deoptimr-1.0_8-r343h889e2dd_0.tar.bz2  6 years and 2 months ago 1 main
conda 51.5 kB | win-64/r-deoptimr-1.0_8-r351h6f4ce42_0.tar.bz2  6 years and 2 months ago 6 main
conda 52.0 kB | win-64/r-deoptimr-1.0_8-r343h889e2dd_0.tar.bz2  6 years and 2 months ago 1 main

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