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[](http://nlopt.readthedocs.io/en/latest/)
[](https://github.com/stevengj/nlopt/actions/workflows/build.yml)
NLopt is a library for nonlinear local and global optimization, for
functions with and without gradient information. It is designed as
a simple, unified interface and packaging of several free/open-source
nonlinear optimization libraries.
The latest release can be downloaded from the [NLopt releases](https://github.com/stevengj/nlopt/releases) page on Github, and the
[NLopt manual](
https://nlopt.readthedocs.io/en/latest/) is hosted on readthedocs.
NLopt is compiled and installed with the [CMake](https://cmake.org/) build system
(see `CMakeLists.txt` file for available options):
git clone https://github.com/stevengj/nlopt.git
cd nlopt
mkdir build
cd build
cmake ..
make
sudo make install
(To build the latest development sources from git, you will need [SWIG](http://www.swig.org/)
to generate the Python and Guile bindings.)
Once it is installed, `#include <nlopt.h>` in your C/C++ programs and
link it with `-lnlopt -lm`. You may need to use a C++ compiler to link
in order to include the C++ libraries (which are used internally by NLopt,
even though it exports a C API). See the [C reference manual](https://nlopt.readthedocs.io/en/latest/NLopt_Reference/).
There are also interfaces for [C++](https://nlopt.readthedocs.io/en/latest/NLopt_C-plus-plus_Reference/), [Fortran](https://nlopt.readthedocs.io/en/latest/NLopt_Fortran_Reference/), [Python](https://nlopt.readthedocs.io/en/latest/NLopt_Python_Reference/), [Matlab or GNU Octave](https://nlopt.readthedocs.io/en/latest/NLopt_Matlab_Reference/), [OCaml](https://bitbucket.org/mkur/nlopt-ocaml),
[GNU Guile](https://nlopt.readthedocs.io/en/latest/NLopt_Guile_Reference/), [GNU R](https://www.ucl.ac.uk/~uctpjyy/nloptr.html), [Lua](https://github.com/rochus-keller/LuaNLopt), [Rust](https://github.com/jesskfullwood/rust-nlopt), and [Julia](https://github.com/JuliaOpt/NLopt.jl). Interfaces for other languages may
be added in the future.
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