Features โข Installation โข License โข Documentation

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

with decision variables

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

Clarabel is also available in a Rust implementation with additional language interfaces. See here.

**Versatile**: Clarabel.jl 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.jl 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.**JuMP / Convex.jl support**: We provide an interface to MathOptInterface (MOI), which allows you to describe your problem in JuMP and Convex.jl.**Arbitrary precision types**: You can solve problems with any floating point precision, for example, Float32 or Julia's BigFloat type, using either the native interface, or via MathOptInterface / Convex.jl.**Open Source**: Our code is available on GitHub and distributed under the Apache 2.0 License

**Clarabel.jl**can be added via the Julia package manager (type`]`

):`pkg> add Clarabel`

```
@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.