https://github.com/pharosabad/lightenqp.jl

A pure Julia implementation of OOQP
https://github.com/pharosabad/lightenqp.jl

interior-point-algorithms quadratic-programming

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A pure Julia implementation of OOQP

• Host: GitHub
• URL: https://github.com/pharosabad/lightenqp.jl
• Owner: PharosAbad
• License: mit
• Created: 2023-01-19T17:30:46.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2023-05-10T03:37:25.000Z (about 3 years ago)
• Last Synced: 2025-10-21T12:03:28.274Z (7 months ago)
• Topics: interior-point-algorithms, quadratic-programming
• Language: Julia
• Homepage:
• Size: 47.9 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
___LightenQP.jl___

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  A pure Julia implementation of OOQP





  Features •

  Installation •

  License •

  Documentation



**LightenQP.jl** solves the following convex quadratic programming problems (called `OOQP`):

$$

\begin{array}

[c]{cl}

\min & \frac{1}{2}\mathbf{x}^{\prime}\mathbf{Vx}+\mathbf{x}^{\prime}%

\mathbf{q}\\

s.t. & \mathbf{Ax}=\mathbf{b}\in\mathbb{R}^{M}\\

& \mathbf{Cx}\leq\mathbf{g}\in\mathbb{R}^{L}

\end{array}

$$

with positive semi-definite symmetric matrix $\mathbf{V}\in\mathbb{R}^{N\times N}$. The general quadratic programming formulation solved by `LightenQP` is (`OOQP + d≤x≤u + h≤Cx`)

$$

\begin{array}

[c]{cl}

\min & \frac{1}{2}\mathbf{x}^{\prime}\mathbf{Vx}+\mathbf{x}^{\prime}

\mathbf{q}\\

s.t. & \mathbf{Ax}=\mathbf{b}\in\mathbb{R}^{M}\\

& \mathbf{h}\leq\mathbf{Cx}\leq\mathbf{g}\in\mathbb{R}^{L}\\

& \boldsymbol{d}\leq\mathbf{x}\leq\boldsymbol{u}\in\mathbb{R}^{N}

\end{array}

$$

## Features

* __Light Weight__: 100+ lines Julia code. Which follows closely the the implementation of the C/C++ solver [OOQP](https://github.com/emgertz/OOQP)

* __Fast__:  [Speed and Accuracy](https://github.com/PharosAbad/LightenQP.jl/wiki/Speed-and-Accuracy)

* __Versatile__: solving a general quadratic programming problem mentioned above. $\mathbf{V}$ can be positive definite or positive semi-definite

* __Open Source__: Our code is available on [GitHub](https://github.com/PharosAbad/LightenQP.jl) and distributed under the MIT License

* __Arbitrary Precision Arithmetic__: fully support for `BigFloat`

## Installation

__LightenQP.jl__ can be added by

- `import Pkg; Pkg.add("LightenQP")`

- `pkg> add LightenQP`

- `pkg> dev LightenQP` for testing nightly version. To use the registered version again `pkg> free LightenQP`

## License 🔍

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.