xega: Extended Evolutionary and Genetic Algorithms
Implementation of a scalable, highly configurable, and e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms. Multiple representations (binary, real-coded, permutation, and derivation-tree), a rich collection of genetic operators, as well as an extended processing pipeline are provided for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)), differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) <doi:10.1007/3-540-31306-0>), simulated annealing (Aarts, E., and Korst, J. (1989, ISBN:0-471-92146-7)), grammar-based genetic programming (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), grammatical evolution (Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>), and grammatical differential evolution (O'Neill, M. and Brabazon, A. (2006) in Arabinia, H. (2006, ISBN:978-193-241596-3). All algorithms reuse basic adaptive mechanisms for performance optimization. For xega's architecture, see Geyer-Schulz, A. (2025) <doi:10.5445/IR/1000187255>. Sequential or parallel execution (on multi-core machines, local clusters, and high-performance computing environments) is available for all algorithms. See <https://github.com/ageyerschulz/xega/tree/main/examples/executionModel>.
| Version: | 0.9.0.18 |
| Depends: | R (≥ 3.5.0),parallelly,filelock |
| Imports: | xegaSelectGene,xegaBNF,xegaDerivationTrees,xegaGaGene,xegaGpGene,xegaGeGene,xegaDfGene,xegaPermGene,xegaPopulation |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-11-28 |
| DOI: | 10.32614/CRAN.package.xega |
| Author: | Andreas Geyer-Schulz [aut, cre] |
| Maintainer: | Andreas Geyer-Schulz <Andreas.Geyer-Schulz at kit.edu> |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/ageyerschulz/xega |
| NeedsCompilation: | no |
| Citation: | xega citation info |
| Materials: | README,NEWS |
| CRAN checks: | xega results |
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