Package: DEoptimR 1.1-3-1
DEoptimR: Differential Evolution Optimization in Pure R
Differential Evolution (DE) stochastic heuristic algorithms for global optimization of problems with and without general constraints. The aim is to curate a collection of its 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 provides implementations of the algorithms 'jDE' by Brest et al. (2006) <doi:10.1109/TEVC.2006.872133> for single-objective optimization and 'NCDE' by Qu et al. (2012) <doi:10.1109/TEVC.2011.2161873> for multimodal optimization (single-objective problems with multiple solutions).
Authors:
DEoptimR_1.1-3-1.tar.gz
DEoptimR_1.1-3-1.zip(r-4.5)DEoptimR_1.1-3-1.zip(r-4.4)DEoptimR_1.1-3-1.zip(r-4.3)
DEoptimR_1.1-3-1.tgz(r-4.5-any)DEoptimR_1.1-3-1.tgz(r-4.4-any)DEoptimR_1.1-3-1.tgz(r-4.3-any)
DEoptimR_1.1-3-1.tar.gz(r-4.5-noble)DEoptimR_1.1-3-1.tar.gz(r-4.4-noble)
DEoptimR_1.1-3-1.tgz(r-4.4-emscripten)DEoptimR_1.1-3-1.tgz(r-4.3-emscripten)
DEoptimR.pdf |DEoptimR.html✨
DEoptimR/json (API)
NEWS
| # Install 'DEoptimR' in R: |
| install.packages('DEoptimR', repos = c('https://eduardotrincaoconceicao.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 months agofrom:0ad3d4dd53. Checks:4 OK, 4 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 22 2025 |
| R-4.5-win | OK | Feb 22 2025 |
| R-4.5-mac | OK | Feb 22 2025 |
| R-4.5-linux | OK | Feb 22 2025 |
| R-4.4-win | NOTE | Feb 22 2025 |
| R-4.4-mac | NOTE | Feb 22 2025 |
| R-4.3-win | NOTE | Feb 22 2025 |
| R-4.3-mac | NOTE | Feb 22 2025 |
Dependencies:
