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alpaqa is an efficient implementation of an augmented Lagrangian method forgeneral nonlinear programming problems, which uses the first-order, matrix-freePANOC algorithm as an inner solver.
The numerical algorithms themselves are implemented in C++ for optimalperformance, and they are exposed as an easy-to-use Python package. Anexperimental MATLAB interface is available as well.

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

$$\begin{equation}\begin{aligned}& \underset{x}{\textbf{minimize}}& & f(x) &&&& f : {\rm I\!R}^n \rightarrow {\rm I\!R} \\& \textbf{subject to}& & \underline{x} \le x \le \overline{x} \\&&& \underline{z} \le g(x) \le \overline{z} &&&& g : {\rm I\!R}^n \rightarrow {\rm I\!R}^m\end{aligned}\end{equation}$$

• Documentation (Sphinx)
• Python examples
• C++ documentation (Doxygen)
• C++ examples
• Matlab documentation

The Python interface can be installed directly fromPyPI:

python3 -m pip install --upgrade --pre alpaqa

For more information, please see the fullinstallation instructions.

Pieter Pas, Mathijs Schuurmans, and Panagiotis Patrinos.Alpaqa: A matrix-free solver for nonlinear MPC and large-scale nonconvex optimization. In2022 European Control Conference (ECC), pages 417–422, 2022.