genetic.algo.optimizeR: Genetic Algorithm Optimization

Genetic algorithm are a class of optimization algorithms inspired by the process of natural selection and genetics. This package is for learning purposes and allows users to optimize various functions or parameters by mimicking biological evolution processes such as selection, crossover, and mutation. Ideal for tasks like machine learning parameter tuning, mathematical function optimization, and solving combinatorial problems.

Version: 0.2.6
Imports: dplyr, ggplot2, magrittr, rsconnect, stats, stringr, tinytex, biocViews
Suggests: BiocStyle, knitr, learnr, rmarkdown, spelling, testthat (≥ 3.0.0)
Published: 2024-02-15
Author: Dany Mukesha ORCID iD [aut, cre]
Maintainer: Dany Mukesha <danymukesha at gmail.com>
BugReports: https://github.com/danymukesha/genetic.algo.optimizeR/issues
License: MIT + file LICENSE
URL: https://danymukesha.github.io/genetic.algo.optimizeR/, https://github.com/danymukesha/genetic.algo.optimizeR
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: genetic.algo.optimizeR results

Documentation:

Reference manual: genetic.algo.optimizeR.pdf
Vignettes: Explaining Graph
Introduction
Theory

Downloads:

Package source: genetic.algo.optimizeR_0.2.6.tar.gz
Windows binaries: r-devel: genetic.algo.optimizeR_0.2.6.zip, r-release: genetic.algo.optimizeR_0.2.6.zip, r-oldrel: genetic.algo.optimizeR_0.2.6.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): genetic.algo.optimizeR_0.2.6.tgz
Old sources: genetic.algo.optimizeR archive

Linking:

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