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>.
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curl https://depscope.dev/api/check/conda/r-deoptimrFirst published · 2021-05-24 08:23:29.864000+00:00
Last updated · 2025-09-10 07:57:56.238000+00:00