DifferentialEvolution: Global optimization using Differential Evolution
Plain Differential Evolution algorithm for optimizing real-valued functions. For further info, see Differential evolution: a practical approach to global optimization By Kenneth V. Price, Rainer M. Storn, and Jouni A. Lampinen.
This Library is optimized and should achieve runtimes with factor of 2 from c. For optimal performance, pay some attention to rts memory parameters.
Example in GHCi:
import Data.Vector.Unboxed as VUB import Numeric.Optimization.Algorithms.DifferentialEvolution let fitness = VUB.sum . VUB.map (*2) de (defaultParams fitness ((VUB.replicate 60 0), (VUB.replicate 60 0)))
Modules
- Numeric
- Optimization
- Algorithms
- Numeric.Optimization.Algorithms.DifferentialEvolution
- Algorithms
- Optimization
Downloads
- DifferentialEvolution-0.0.2.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
Maintainer's Corner
For package maintainers and hackage trustees
Candidates
- No Candidates
Versions [RSS] | 0.0.1, 0.0.2 |
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Dependencies | base (>=4 && <5), deepseq (>=1.1 && <2), fclabels (>=0.11 && <0.12), mtl (>2 && <=3), mwc-random (>=0.8 && <0.9), parallel (>=3.1 && <4), primitive (>=0.3.1 && <4), vector (>=0.7 && <0.8) [details] |
License | MIT |
Author | Ville Tirronen |
Maintainer | ville.tirronen@jyu.fi |
Category | Numerical, Optimization, Algorithms |
Home page | http://yousource.it.jyu.fi/optimization-with-haskell |
Uploaded | by VilleTirronen at 2011-03-11T11:59:14Z |
Distributions | |
Reverse Dependencies | 1 direct, 0 indirect [details] |
Downloads | 2295 total (1 in the last 30 days) |
Rating | (no votes yet) [estimated by Bayesian average] |
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Status | Docs not available [build log] All reported builds failed as of 2016-10-25 [all 15 reports] |