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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>.

copied from cf-staging / r-deoptimr
Type Size Name Uploaded Downloads Labels
conda 60.1 kB | noarch/r-deoptimr-1.0_14-r42hc72bb7e_1.conda  1 year and 8 months ago 1662 main
conda 60.4 kB | noarch/r-deoptimr-1.0_14-r43hc72bb7e_1.conda  1 year and 8 months ago 1305 main
conda 60.3 kB | noarch/r-deoptimr-1.0_14-r41hc72bb7e_0.conda  1 year and 8 months ago 4445 main
conda 60.4 kB | noarch/r-deoptimr-1.0_14-r42hc72bb7e_0.conda  1 year and 8 months ago 1223 main

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