Documentation and API reference (MOSEK version 8.1)
| General | Introduction | Installation | Licensing | Release notes | FAQ |
| Fusion API | C++ | Java | .NET | Python | MATLAB |
| Optimizer API | C | Java | .NET | Python | |
| Other interfaces | Toolbox (MATLAB) | Rmosek (R) | Command line | OptServer |
Documentation for older versions is included with the distribution.
Additional technical documentation
- FlexNet License Administration Guide (PDF) - the detailed license system guide for advanced users. For most users the MOSEK licensing guide above should be sufficient.
Modeling
- The MOSEK Modeling Cookbook (HTML) - is a mathematically oriented publication about conic optimization which presents the theory, examples and many tips and tricks about formulating optimization problems. Also available as PDF (A4) and PDF (letter).
- Portfolio Optimization with MOSEK - a collection of portfolio optimization models using the Optimizer and Fusion API.
- Conic Modeling Cheatsheet (PDF).
The MOSEK Notebook Collection
A collection of tutorials which demonstrate how to model and solve various optimization problems with MOSEK. Further case studies can be found in the documentation and on MOSEK GitHub.
| Title | Type | Tools | Keywords |
|---|---|---|---|
| An introduction to Fusion | LO, CQO | Python, Fusion | |
| Filter design | SDO | Python, Fusion | trigonometric polynomials, Czebyshev lowpass filter |
| Geometric facility location | MICQO | Python, Fusion | planar coverage, wireless network design |
| Linear regression | CQO | Python, Fusion | Lp-norm, rotated cone |
| Risk parity portfolio selection | SCOPT | Python | fully invested portfolio |
| Smallest enclosing sphere | CQO | Python, Fusion | geometry, dualization |
| Optimization of cycles on surfaces | LO | Python, Fusion | geometry, topology, triangulation |
| Equilibrium of masses with springs | CQO | Python, Fusion | mechanical equilibrium, potential energy |
| Unit commitment | MICQO | Python, Fusion | unit commitment, production planning |
| Least squares regression | CQO | Python, Fusion | least squares, regularization, lasso, ridge, robust Huber loss |
| Exact planar cover | MIO | Python | combinatorial, binary variables, relaxation, certificate |
| Binary quadratic problems | QP, SDP | Python, Fusion | SDP relaxation, branch and bound, binary QP |
Publications and Technical Reports
| Title | Assoc. files | Date | Rev. date |
|---|---|---|---|
| Regression techniques for Portfolio Optimisation using MOSEK | 21-oct-2013 | ||
| On formulating quadratic functions in optimization models | 04-dec-2014 | 02-mar-2016 | |
| How to use Farkas' lemma to say something important about infeasible linear problems | 12-sep-2011 | ||
| Markowitz portfolio optimization using MOSEK | Data and code | 02-jun-2009 | 14-feb-2012 |
| The homogeneous and self-dual model and algorithm for linear optimization | 21-oct-2013 | ||
| MOSEK related publications | 19-aug-2011 |
