GA

An R package for optimization using genetic algorithms

https://github.com/luca-scr/ga

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords

genetic-algorithm optimisation r
Last synced: 6 months ago · JSON representation

Repository

An R package for optimization using genetic algorithms

Basic Info
Statistics
  • Stars: 93
  • Watchers: 5
  • Forks: 30
  • Open Issues: 14
  • Releases: 0
Topics
genetic-algorithm optimisation r
Created over 10 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

GA

CRAN\_Status\_Badge CRAN\_MonthlyDownloads

An R package for stochastic optimisation using Genetic Algorithms.

The GA package provides a flexible general-purpose set of tools for implementing genetic algorithms search in both the continuous and discrete case, whether constrained or not. Users can easily define their own objective function depending on the problem at hand. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach.

Installation

You can install the released version of GA from CRAN:

r install.packages("GA")

or the development version from GitHub:

```r

install.packages("devtools")

devtools::installgithub("luca-scr/GA", build = TRUE, buildopts = c("--no-resave-data", "--no-manual")) ```

Usage

Usage of the main functions and several examples are included in the papers shown in the references section below.

For an intro see the vignette A quick tour of GA, which is available as

r vignette("GA")

The vignette is also available in the Get Started section on the GitHub web page of the package at http://luca-scr.github.io/GA/.

References

Scrucca, L. (2013) GA: A Package for Genetic Algorithms in R. Journal of Statistical Software, 53/4, 1-37. https://doi.org/10.18637/jss.v053.i04

Scrucca, L. (2017) On some extensions to GA package: hybrid optimisation, parallelisation and islands evolution. The R Journal, 9/1, 187–206. https://doi.org/10.32614/RJ-2017-008

Owner

  • Name: Luca Scrucca
  • Login: luca-scr
  • Kind: user
  • Location: Perugia, Italy
  • Company: University of Perugia

GitHub Events

Total
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 10
  • Pull request event: 1
  • Fork event: 2
Last Year
  • Issues event: 2
  • Watch event: 3
  • Issue comment event: 10
  • Pull request event: 1
  • Fork event: 2

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 49
  • Total Committers: 3
  • Avg Commits per committer: 16.333
  • Development Distribution Score (DDS): 0.286
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
luca-scr l****a@u****t 35
luca-scr l****a@s****t 13
Luca Scrucca l****a@s****t 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 57
  • Total pull requests: 6
  • Average time to close issues: 4 months
  • Average time to close pull requests: about 2 months
  • Total issue authors: 45
  • Total pull request authors: 6
  • Average comments per issue: 1.98
  • Average comments per pull request: 1.83
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • maxrodkin (5)
  • swaheera (4)
  • tamas-ferenci (2)
  • dslate1 (2)
  • fxdlmatt (2)
  • neverfox (2)
  • JasonCEC (2)
  • NedaJalali-codes (1)
  • enriquegit (1)
  • watashiwa-toki (1)
  • andyjslee (1)
  • oujbih (1)
  • fabiansiuda (1)
  • Paul-AntoineLeboeuf (1)
  • kk-1 (1)
Pull Request Authors
  • RomeroBarata (1)
  • linanqiu (1)
  • yutannihilation (1)
  • ebyerly (1)
  • JosHageman (1)
  • charliec443 (1)
  • yacine-benahmed (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • cran 6,493 last-month
  • Total docker downloads: 46,254
  • Total dependent packages: 46
    (may contain duplicates)
  • Total dependent repositories: 63
    (may contain duplicates)
  • Total versions: 19
  • Total maintainers: 1
cran.r-project.org: GA

Genetic Algorithms

  • Versions: 15
  • Dependent Packages: 46
  • Dependent Repositories: 62
  • Downloads: 6,493 Last month
  • Docker Downloads: 46,254
Rankings
Dependent packages count: 1.8%
Forks count: 2.8%
Dependent repos count: 3.1%
Stargazers count: 4.3%
Downloads: 5.8%
Average: 7.3%
Docker downloads count: 25.8%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: r-ga
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 1
Rankings
Dependent repos count: 24.3%
Forks count: 31.9%
Stargazers count: 35.0%
Average: 35.7%
Dependent packages count: 51.6%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.4 depends
  • foreach * depends
  • iterators * depends
  • methods * depends
  • Rcpp * imports
  • cli * imports
  • crayon * imports
  • grDevices * imports
  • graphics * imports
  • stats * imports
  • utils * imports
  • doParallel * suggests
  • doRNG >= 1.6 suggests
  • knitr >= 1.8 suggests
  • parallel * suggests
  • rmarkdown >= 2.0 suggests