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rmoo: Multi-Objective Optimization in R

The 'rmoo' package is a framework for multi- and many-objective optimization, which allows researchers and users versatility in parameter configuration, as well as tools for analysis, replication and visualization of results. The 'rmoo' package was built as a fork of the 'GA' package by Luca Scrucca(2017) <doi:10.32614/RJ-2017-008> and implementing the Non-Dominated Sorting Genetic Algorithms proposed by K. Deb's.

Version: 0.2.0
Depends: R (≥ 2.10)
Imports: stats, utils, graphics, methods, GA, grDevices, ggplot2, plotly
Suggests: testthat, covr, rgl, ecr, emoa, cdata, dplyr, reshape2
Published: 2022-09-24
DOI: 10.32614/CRAN.package.rmoo
Author: Francisco Benitez [aut, cre], Diego Pinto Roa ORCID iD [aut]
Maintainer: Francisco Benitez <benitezfj94 at gmail.com>
BugReports: https://github.com/Evolutionary-Optimization-Laboratory/rmoo/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/Evolutionary-Optimization-Laboratory/rmoo/
NeedsCompilation: no
Language: es
Materials: README
In views: Optimization
CRAN checks: rmoo results

Documentation:

Reference manual: rmoo.pdf

Downloads:

Package source: rmoo_0.2.0.tar.gz
Windows binaries: r-devel: rmoo_0.2.0.zip, r-release: rmoo_0.2.0.zip, r-oldrel: rmoo_0.2.0.zip
macOS binaries: r-release (arm64): rmoo_0.2.0.tgz, r-oldrel (arm64): rmoo_0.2.0.tgz, r-release (x86_64): rmoo_0.2.0.tgz, r-oldrel (x86_64): rmoo_0.2.0.tgz
Old sources: rmoo archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.