Introduction

This is a C implementation of QPALM, a proximal augmented Lagrangian based solver for (possibly nonconvex) quadratic programs. QPALM solves problems of the form:

\begin{align*} & \operatorname*{\mathrm{minimize}}_x & & \tfrac{1}{2}x^\top Q x + q^\top x \\ & \text{subject to} & & b_\mathrm{min} \leq Ax \leq b_\mathrm{max} \end{align*}

Installation instructions

Python

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

python3 -m pip install qpalm

Julia

In the Julia console, press ] to enter the Pkg REPL and install QPALM using:

add QPALM

C/C++/Fortran

Pre-built C, C++ and Fortran libraries for Linux are available from the releases page.

Matlab

Pre-built Matlab binaries are available from the releases page. Download the version for your system and extract it into the ~/Documents/MATLAB folder.

As a one-liner in the Matlab console:

unzip('https://github.com/kul-optec/QPALM/releases/download/1.1.1/qpalm-matlab-linux.zip', userpath)

unzip('https://github.com/kul-optec/QPALM/releases/download/1.1.1/qpalm-matlab-windows.zip', userpath)

Building QPALM from source

For the full instructions to build QPALM from source, please see the Installation instructions.

Code examples

Python interface: examples/python/qpalm_python_demo.py
Julia interface: examples/julia/qpalm_julia_demo.jl
C++ interface: examples/cxx/qpalm_demo.cpp
Fortran interface: examples/fortran/qpalm_fortran_demo.f90
C API: examples/c/qpalm_demo.c
Matlab MEX interface: examples/matlab/qpalm_mex_demo.m and examples/matlab/qpalm_mex_nonconvex_demo.m

Citing QPALM

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.},
}

License

LGPL-3.0