Differential Evolution Optimization in Pure R

Differential Evolution (DE) stochastic algorithms for global optimization of problems with and without constraints. The aim is to curate a collection of its state-of-the-art variants that (1) do not sacrifice simplicity of design, (2) are essentially tuning-free, and (3) can be efficiently implemented directly in the R language. Currently, it only provides an implementation of the 'jDE' algorithm by Brest et al. (2006) .


News

  CHANGES IN DEoptimR VERSION 1.0-0

NEW FEATURES

  • First release of DEoptimR: implementation of a variant of the jDE algorithm.

  • Constraint handling based on biasing feasible over unfeasible solutions by a parameter-less variant of the epsilon-constrained method.

Reference manual

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install.packages("DEoptimR")

1.0-8 by Eduardo L. T. Conceicao, 3 years ago


Browse source code at https://github.com/cran/DEoptimR


Authors: Eduardo L. T. Conceicao [aut, cre] , Martin Maechler [ctb]


Documentation:   PDF Manual  


Task views: Optimization and Mathematical Programming


GPL (>= 2) license


Imports stats

Enhances robustbase


Imported by ROI.plugin.deoptim, RobStatTM, robustbase.

Suggested by MSCMT.


See at CRAN