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 an optimization problem that involves finding the best solution in a discrete space.

Version:	0.3.2
Imports:	dplyr, ggplot2, magrittr, rsconnect, stats, stringr, tinytex, biocViews, DiagrammeR
Suggests:	BiocStyle, knitr, learnr, rmarkdown, spelling, testthat (≥ 3.0.0)
Published:	2024-10-10
DOI:	10.32614/CRAN.package.genetic.algo.optimizeR
Author:	Dany Mukesha [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 [issues need fixing before 2024-11-04]

Documentation:

Reference manual:	genetic.algo.optimizeR.pdf
Vignettes:	Introduction to genetic.algo.optimizeR (source, R code) Optimization of a Quadratic Function Using Genetic Algorithms (source, R code)

Downloads:

Package source:	genetic.algo.optimizeR_0.3.2.tar.gz
Windows binaries:	r-devel: genetic.algo.optimizeR_0.3.2.zip, r-release: genetic.algo.optimizeR_0.3.2.zip, r-oldrel: genetic.algo.optimizeR_0.3.2.zip
macOS binaries:	r-release (arm64): genetic.algo.optimizeR_0.3.2.tgz, r-oldrel (arm64): not available, r-release (x86_64): genetic.algo.optimizeR_0.3.2.tgz, r-oldrel (x86_64): genetic.algo.optimizeR_0.3.2.tgz
Old sources:	genetic.algo.optimizeR archive

Linking:

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