Mj23366 08d5a1f4cc first commit 2 months ago
..
build 08d5a1f4cc first commit 2 months ago
ci 08d5a1f4cc first commit 2 months ago
configure 08d5a1f4cc first commit 2 months ago
examples 08d5a1f4cc first commit 2 months ago
include 08d5a1f4cc first commit 2 months ago
lin_sys 08d5a1f4cc first commit 2 months ago
src 08d5a1f4cc first commit 2 months ago
tests 08d5a1f4cc first commit 2 months ago
.bumpversion.cfg 08d5a1f4cc first commit 2 months ago
.editorconfig 08d5a1f4cc first commit 2 months ago
.gitattributes 08d5a1f4cc first commit 2 months ago
.gitmodules 08d5a1f4cc first commit 2 months ago
.travis.yml 08d5a1f4cc first commit 2 months ago
.valgrind-suppress.supp 08d5a1f4cc first commit 2 months ago
CHANGELOG.md 08d5a1f4cc first commit 2 months ago
CMakeLists.txt 08d5a1f4cc first commit 2 months ago
LICENSE 08d5a1f4cc first commit 2 months ago
NOTICE 08d5a1f4cc first commit 2 months ago
README.md 08d5a1f4cc first commit 2 months ago
ROADMAP.md 08d5a1f4cc first commit 2 months ago
appveyor.yml 08d5a1f4cc first commit 2 months ago
make 08d5a1f4cc first commit 2 months ago

README.md

The Operator Splitting QP Solver

Build status of the master branch on Linux/OSX Build status of the master branch on Windows Code coverage License

PyPI - downloads Conda - downloads

Join our forum on Discourse for any questions related to the solver!

The documentation is available at osqp.org

The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form

minimize        0.5 x' P x + q' x

subject to      l <= A x <= u

where x in R^n is the optimization variable. The objective function is defined by a positive semidefinite matrix P in S^n_+ and vector q in R^n. The linear constraints are defined by matrix A in R^{m x n} and vectors l and u so that l_i in R U {-inf} and u_i in R U {+inf} for all i in 1,...,m.

The latest version is 0.6.0.

Citing OSQP

If you are using OSQP for your work, we encourage you to

We are looking forward to hearing your success stories with OSQP! Please share them with us.

Bug reports and support

Please report any issues via the Github issue tracker. All types of issues are welcome including bug reports, documentation typos, feature requests and so on.

Numerical benchmarks

Numerical benchmarks against other solvers are available here.