Package: genetic.algo.optimizeR 0.3.2

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.
Authors:
genetic.algo.optimizeR_0.3.2.tar.gz
genetic.algo.optimizeR_0.3.2.zip(r-4.7)genetic.algo.optimizeR_0.3.2.zip(r-4.6)genetic.algo.optimizeR_0.3.2.zip(r-4.5)
genetic.algo.optimizeR_0.3.2.tgz(r-4.6-any)genetic.algo.optimizeR_0.3.2.tgz(r-4.5-any)
genetic.algo.optimizeR_0.3.2.tar.gz(r-4.7-any)genetic.algo.optimizeR_0.3.2.tar.gz(r-4.6-any)
genetic.algo.optimizeR_0.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
genetic.algo.optimizeR/json (API)
NEWS
| # Install 'genetic.algo.optimizeR' in R: |
| install.packages('genetic.algo.optimizeR', repos = c('https://danymukesha.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/danymukesha/genetic.algo.optimizer/issues
Pkgdown/docs site:https://danymukesha.github.io
Last updated from:1a2a1a1899. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 187 | ||
| source / vignettes | OK | 243 | ||
| linux-release-x86_64 | OK | 184 | ||
| macos-release-arm64 | OK | 163 | ||
| macos-oldrel-arm64 | OK | 263 | ||
| windows-devel | OK | 134 | ||
| windows-release | OK | 133 | ||
| windows-oldrel | OK | 115 | ||
| wasm-release | OK | 153 |
Exports:crossoverevaluate_fitnessinitialize_populationmutationreplacementselection
Dependencies:askpassbase64encBHBiobaseBiocGenericsBiocManagerbiocViewsbitbit64bitopsbslibcachemclicliprcpp11crayoncurlDiagrammeRdigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegraphgtablehighrhmshtmltoolshtmlwidgetshttr2igraphisobandjosejquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimeopensslpackratpillarpkgconfigPKIprettyunitsprogresspurrrR6rappdirsRBGLRColorBrewerRcppRcppTOMLRCurlreadrrenvrlangrmarkdownrsconnectrstudioapiRUnitS7sassscalessnowflakeauthstringistringrsystibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunXMLyaml
Introduction to genetic.algo.optimizeR
Rendered fromintro_to_genetic.algo.optimizeR.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2024-10-07
Started: 2024-10-07
Optimization of a Quadratic Function Using Genetic Algorithms
Rendered fromoptimize_function_with_GA.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2024-10-07
Started: 2024-10-07
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Crossover of selected parents from the fitting population | crossover |
| Evaluating the fitness of the population | evaluate_fitness |
| Initialize population | initialize_population |
| Mutating the offspring | mutation |
| Replacing non-selected individual(s) | replacement |
| Selecting the fitting the population | selection |
