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 [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
Dependencies base (>=3 && <5), primitive (>=0.2 && <0.8), vector (>=0.5 && <=0.13) [details]
License LicenseRef-GPL
Copyright (c) 2010-2011 Felipe A. Lessa and William W. Hager
Author Felipe A. Lessa (Haskell code), William W. Hager and Hongchao Zhang (CM_DESCENT code).
Maintainer Felipe A. Lessa <felipe.lessa@gmail.com>
Category Math
Home page https://github.com/meteficha/nonlinear-optimization
Bug tracker https://github.com/meteficha/nonlinear-optimization/issues
Source repo head: git clone https://github.com/meteficha/nonlinear-optimization
Uploaded by FelipeLessa at 2020-03-01T13:29:42Z
Distributions NixOS:0.3.12.1
Downloads 11159 total (50 in the last 30 days)
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Status Hackage Matrix CI
Docs available [build log]
Last success reported on 2020-03-01 [all 1 reports]

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