R Programming/Optimization


 * optimize is devoted to one dimensional optimization problem.
 * optim, nlm, ucminf (ucminf) can be used for multidimensional optimization problems.
 * nlminb for constrained optimization.
 * quadprog, minqa, rgenoud, trust packages
 * Some work is done to improve optimization in R. See Updating and improving optim, Use R 2009 slides, the R-forge optimizer page and the corresponding packages including optimx.

One dimensional problem
The one dimensional problem :

Newton-Raphson

 * nlm provides a Newton algorithm.
 * maxLik package for maximization of a likelihood function. This package includes the Newton Raphson method.
 * newtonraphson in the spuRs package.

BFGS

 * The BFGS method

Conjugate gradient method

 * with.

Trust Region Method

 * "trust" package for trust region method

The Nelder-Mead simplex method

 * The Nelder Mead Method


 * The boot package includes another simplex method

Simulated Annealing

 * The Simulated Annealing is an algorithm which is useful to maximise non-smooth functions. It is pre implemented in optim.

Genetic Algorithm

 * rgenoud package for genetic algorithm
 * gaoptim package for genetic algorithm
 * ga general purpose package for optimization using genetic algorithms. It provides a flexible set of tools for implementing genetic algorithms search in both the continuous and discrete case, whether constrained or not.