GA: Genetic Algorithms. An R package for optimization using genetic algorithms. The 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. GAs can be run sequentially or in parallel.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Galimberti, Giuliano; Manisi, Annamaria; Soffritti, Gabriele: Modelling the role of variables in model-based cluster analysis (2018)
- Ordóñez Galán, Celestino; Sánchez Lasheras, Fernando; de Cos Juez, Francisco Javier; Bernardo Sánchez, Antonio: Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions (2017)
- Christian Panse: Rectangular Statistical Cartograms in R: The recmap Package (2016) arXiv
- Dirick, Lore; Claeskens, Gerda; Baesens, Bart: An Akaike information criterion for multiple event mixture cure models (2015)
- Nash, John C.: Nonlinear parameter optimization using R tools (2014)