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Library for nonconvex constrained optimization using the augmented Lagrangian method and the matrix-free PANOC algorithm.

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alpaqa

Alpaqa is an efficient implementation of the Augmented Lagrangian method for general nonlinear programming problems, which uses the first-order, matrix-free PANOC algorithm as an inner solver.
The numerical algorithms themselves are implemented in C++ for optimal performance, and they are exposed as an easy-to-use Python package.

The solvers in this library solve minimization problems of the following form:

Problem formulation

The objective function f(x) and the constraints function g(x) should have a Lipschitz-continuous gradient.

Documentation

Sphinx documentation
Doxygen documentation
Python examples
C++ examples

Installation

The project is available on PyPI:

python3 -m pip install alpaqa

For more information, please see the full installation instructions.

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Library for nonconvex constrained optimization using the augmented Lagrangian method and the matrix-free PANOC algorithm.

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  • C++ 75.2%
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