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:
with decision variables
For more information see the Clarabel Documentation (stable | dev).
Clarabel is also available in a Julia implementation. See here.
- 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
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.
@misc{Clarabel_2024,
title={Clarabel: An interior-point solver for conic programs with quadratic objectives},
author={Paul J. Goulart and Yuwen Chen},
year={2024},
eprint={2405.12762},
archivePrefix={arXiv},
primaryClass={math.OC}
}
This project is licensed under the Apache License 2.0 - see the LICENSE.md file for details.