# Data Mining Algorithms In R/Packages/optimsimplex/optimsimplex-package

## Description edit

The goal of this package is to provide a building block for optimization algorithms based on a simplex. The '*optimsimplex* package may be used in the following optimization methods:

- the simplex method of Spendley et al.,
- the method of Nelder and Mead,
- the Box’s algorithm for constrained optimization,
- the multi-dimensional search by Torczon,
- etc ...

### Features edit

The following is a list of features currently provided:

- Manage various simplex initializations

- initial simplex given by user,
- initial simplex computed with a length and along the coordinate axes,

- initial regular simplex computed with Spendley et al. formula,

- initial simplex computed by a small perturbation around the initial guess point,
- initial simplex computed from randomized bounds.

- sort the vertices by increasing function values,
- compute the standard deviation of the function values in the simplex,
- compute the simplex gradient with forward or centered differences,
- shrink the simplex toward the best vertex,
- etc...

## Details edit

Package: | optimsimplex |

Type: | Package |

Version: | 1.0-2 |

Date: | 2010-05-11 |

License: | CeCILL-2 |

LazyLoad: | yes |

## Authors edit

Author of Scilab optimsimplex module: Michael Baudin (INRIA - Digiteo)

Author of R adaptation: Sebastien Bihorel (*sb.pmlab@gmail.com*)