# nonlinear-optimization: Various iterative algorithms for optimization of nonlinear functions.

[ library, math ] [ Propose Tags ]

This library implements numerical algorithms to optimize nonlinear functions. Optimization means that we try to find a minimum of the function. Currently all algorithms guarantee only that local minima will be found, not global ones.

Almost any continuosly differentiable function f : R^n -> R may be optimized by this library. Any further restrictions are listed in the modules that need them.

We use the vector package to represent vectors and matrices, although it would be possible to use something like hmatrix easily.

Currently only CG_DESCENT method is implemented.

If you want to use automatic differentiation to avoid hand-writing gradient functions, you can use nonlinear-optimization-ad package or nonlinear-optimization-backprop package.

Versions [RSS] [faq] 0.1, 0.2, 0.3, 0.3.1, 0.3.2, 0.3.3, 0.3.4, 0.3.5, 0.3.5.1, 0.3.5.2, 0.3.6, 0.3.7, 0.3.8, 0.3.9, 0.3.10, 0.3.11, 0.3.12, 0.3.12.1 base (>=3 && <5), primitive (>=0.2 && <0.8), vector (>=0.5 && <=0.13) [details] LicenseRef-GPL (c) 2010-2011 Felipe A. Lessa and William W. Hager Felipe A. Lessa (Haskell code), William W. Hager and Hongchao Zhang (CM_DESCENT code). Felipe A. Lessa Math https://github.com/meteficha/nonlinear-optimization https://github.com/meteficha/nonlinear-optimization/issues head: git clone https://github.com/meteficha/nonlinear-optimization by FelipeLessa at 2020-03-01T13:29:42Z NixOS:0.3.12.1 11687 total (11 in the last 30 days) (no votes yet) [estimated by Bayesian average] λ λ λ Docs available Last success reported on 2020-03-01

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