clarabel 0.6.0

Clarabel Conic Interior Point Solver for Rust / Python

Interior Point Conic Optimization for Rust and Python

Features • Installation • License • Documentation

Clarabel.rs is a Rust implementation of an interior point numerical solver for convex optimization problems using a novel homogeneous embedding. Clarabel.rs solves the following problem:

$$\begin{array}{rr}\text{minimize}& \frac{1}{2}{x}^{T}Px+q^{T}x\\ \text{subject to}& Ax+s=b\\ & s\in \mathcal{K}\end{array}$$

with decision variables $x\in {\mathbb{R}}^n$, $s\in {\mathbb{R}}^m$ and data matrices $P=P^{\mathrm{\top }}⪰0$, $q\in {\mathbb{R}}^n$, $A\in {\mathbb{R}}^{m\times n}$, and $b\in {\mathbb{R}}^m$. The convex set $\mathcal{K}$ is a composition of convex cones.

For more information see the Clarabel Documentation (stable | dev).

Clarabel is also available in a Julia implementation. See here.

Features

• Versatile: Clarabel.rs solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs) and semidefinite programs (SDPs). It also solves problems with exponential, power cone and generalized power cone constraints.
• Quadratic objectives: Unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE), Clarabel.rs handles quadratic objectives without requiring any epigraphical reformulation of the objective. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions.
• Infeasibility detection: Infeasible problems are detected using a homogeneous embedding technique.
• Open Source: Our code is available on GitHub and distributed under the Apache 2.0 License

Installation

Clarabel can be imported to Cargo based Rust projects by adding

[dependencies]
clarabel = "0"  

to the project's Cargo.toml file. To install from source, see the Rust Installation Documentation.

To use the Python interface to the solver:

pip install clarabel

To install the Python interface from source, see the Python Installation Documentation.

License 🔍

This project is licensed under the Apache License 2.0 - see the LICENSE.md file for details.