Rmalschains: Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R

An implementation of an algorithm family for continuous optimization called memetic algorithms with local search chains (MA-LS-Chains). Memetic algorithms are hybridizations of genetic algorithms with local search methods. They are especially suited for continuous optimization.

Version: 0.2-6
Depends: Rcpp (≥ 0.9.10)
LinkingTo: Rcpp
Suggests: inline
Published: 2019-09-17
Author: Christoph Bergmeir [aut, cre, cph], José M. Benítez [ths], Daniel Molina [aut, cph], Robert Davies [ctb, cph] (Developer of the matrix library newmat which partly ships with this package), Dirk Eddelbuettel [ctb, cph] (Developer of RcppDE from which code was used in evaluate.h), Nikolaus Hansen [ctb, cph] (Author of the original cmaes implementation that ships with the package)
Maintainer: Christoph Bergmeir <c.bergmeir at decsai.ugr.es>
License: GPL-3 | file LICENSE
NeedsCompilation: yes
Citation: Rmalschains citation info
Materials: ChangeLog
In views: MachineLearning, Optimization
CRAN checks: Rmalschains results

Downloads:

Reference manual: Rmalschains.pdf
Package source: Rmalschains_0.2-6.tar.gz
Windows binaries: r-devel: Rmalschains_0.2-6.zip, r-release: Rmalschains_0.2-6.zip, r-oldrel: Rmalschains_0.2-6.zip
OS X binaries: r-release: Rmalschains_0.2-6.tgz, r-oldrel: Rmalschains_0.2-6.tgz
Old sources: Rmalschains archive

Reverse dependencies:

Reverse imports: hybridEnsemble
Reverse suggests: airGR, MSCMT

Linking:

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