AnR package for stochasticoptimisation usingGenetic Algorithms.
TheGA package provides a flexible general-purposeset of tools for implementing genetic algorithms search in both thecontinuous and discrete case, whether constrained or not. Users caneasily define their own objective function depending on the problem athand. Several genetic operators are available and can be combined toexplore the best settings for the current task. Furthermore, users candefine new genetic operators and easily evaluate their performances.Local search using general-purpose optimisation algorithms can beapplied stochastically to exploit interesting regions. GAs can be runsequentially or in parallel, using an explicit master-slaveparallelisation or a coarse-grain islands approach.
You can install the released version ofGA fromCRAN:
install.packages("GA")or the development version from GitHub:
# install.packages("devtools")devtools::install_github("luca-scr/GA", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"))Usage of the main functions and several examples are included in thepapers shown in the references section below.
For an intro see the vignetteA quick tour of GA,which is available as
vignette("GA")The vignette is also available in theGet Started section onthe GitHub web page of the package at http://luca-scr.github.io/GA/.
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: hybridoptimisation, parallelisation and islands evolution.The RJournal, 9/1, 187–206. https://doi.org/10.32614/RJ-2017-008