clarabel.m

MATLAB mex interface to Clarabel, an interior point solver for convex optimization.

Description

This repository contains a (work in progress) MATLAB mex interface to the recently introduced interior point solver Clarabel. The mex interface is interfaced to Clarabel.cpp, the C/C++ interface to the Rust implementation of Clarabel. The interface to the C++ implementation is realized via eigen.

Installation

This version already contains the compiled mex function for Windows (Clarabel 0.9.0) and the needed binaries. MATLAB 2023b and MinGW64 Compiler (C++) was used. On Windows, add the folder to your path. Try the examples in the example folder.

A more detailed description will follow soon such that user can compile it. The major steps for installation:

1. Clone Clarabel.cpp repository, install according to the description (get submodules, get compiler, etc.), and build the project to get libraries (for Windows: clarabel_c.lib, clarabel_c.dll.lib and clarabel_c.dll)
2. Put libraries in the same folder where make_clarabel.m lies.
3. Execute make_clarabel.m to generate the mex file.
4. After the mex file is generated, the clarabel_c.dll must lie in the same folder as the mex function (Windows).

Ensure you have the necessary mex file and libraries set up correctly before runni e.g. the examples provided.

Current Status

The current interface allow to solve all problems except SDPs. In the example folder, the MATLAB implementation of the examples found in the Clarabel.cpp repo are implemented. The current version is kept simple and will be adapted and augmented in the (near) future.

Usage Example

Below is an usage example to showcase solving an optimization problem. The following example simply implements the getting started example for Python via the MATLAB/mex interface. More Examples can be found in the examples folder.

% define cost: 1/2 x^T P x + q^T x
P = sparse(triu([ 3., 1., -1.;
                  1., 4.,  2.;
                 -1., 2.,  5.]));


q = [1., 2., -3.];

% define constraints
Aeq = sparse([1 1 -1]);
beq = 1;

Aineq = sparse([0 1 0; 0 0 1]);
bineq = [2;2];


Asoc = -speye(3);
bsoc = zeros(3,1);

% stack constraints
A = [Aeq;Aineq;Asoc];

b = [beq;bineq;bsoc];

% stack cones
cones = [zeroConeT(1);
         NonnegativeConeT(2);
         SecondOrderConeT(3)];

% generate settings
settings = DefaultSettings();

settings.verbose = false;
settings.time_limit = 5.;

% call interface
sol = clarabel_mex(P,q,A,b,cones,settings)

The order of the cones can be arbitrary similar to the Python interface.