qpalm 1.2.3

Description:

qpalm 1.2.3

QPALM is a numerical optimization package that finds stationary points of (possibly nonconvex) quadratic programs, that is


minimizex12x⊤Qx+q⊤xsubject tobmin≤Ax≤bmax


Documentation

The documentation can be found at: https://kul-optec.github.io/QPALM/Doxygen
Examples are included as well: https://kul-optec.github.io/QPALM/Doxygen/examples.html



Installation

Python

The QPALM Python interface is available from PyPI, you can install it using:

python3 -m pip install qpalm


Julia, Matlab, C/C++/Fortran

Installation instructions for the Julia, Matlab, C, C++ and Fortran interfaces, as well as instructions for building QPALM from source, can be found on GitHub.




Supported platforms

QPALM is written in C, with interfaces for C++, Python, Julia, Matlab and Fortran. The code itself is portable across all major platforms. Binaries are available for Linux on x86-64, AArch64, ARMv7 and ARMv6, for macOS on x86-64 and ARM64, and for Windows on x86-64.



Benchmarks

Check out the papers below for detailed benchmark tests comparing QPALM with state-of-the-art solvers.


QPALM: A Newton-type Proximal Augmented Lagrangian Method for Quadratic Programs.
QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs.



Citing

If you use QPALM in your research, please cite the following paper:

@inproceedings{hermans2019qpalm,
author = {Hermans, B. and Themelis, A. and Patrinos, P.},
booktitle = {58th IEEE Conference on Decision and Control},
title = {{QPALM}: {A} {N}ewton-type {P}roximal {A}ugmented {L}agrangian {M}ethod for {Q}uadratic {P}rograms},
year = {2019},
volume = {},
number = {},
pages = {},
doi = {},
issn = {},
month = {Dec.},
}