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)), and grammatical evolution
(Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>).
All algorithms reuse basic adaptive mechanisms for performance optimization.
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: |
0.9.0.0 |
| Depends: |
R (≥ 3.5.0), parallelly |
| Imports: |
xegaSelectGene, xegaBNF, xegaDerivationTrees, xegaGaGene, xegaGpGene, xegaGeGene, xegaDfGene, xegaPermGene, xegaPopulation |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2024-03-20 |
| Author: |
Andreas Geyer-Schulz
 [aut, cre] |
| Maintainer: |
Andreas Geyer-Schulz <Andreas.Geyer-Schulz at kit.edu> |
| License: |
MIT + file LICENSE |
| URL: |
<https://github.com/ageyerschulz/xega> |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
xega results |
Documentation:
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