Release notes for version 9.3.0.BETA can be found here. For other information refer simply to the 9.2 manuals below.
Documentation and API reference (MOSEK version 9.2)
| General | Introduction | Installation | Licensing | Release notes | FAQ |
| Fusion API | C++ | Java | .NET | Python | |
| Optimizer API | C | Java | .NET | Python | |
| Other interfaces | Toolbox (MATLAB) | Rmosek (R) | Command line | OptServer |
Version 8 user? Please see information about portability in the section Interface changes towards the end of your API's manual. Documentation for version 8.1 is linked at the bottom of this page. 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 |
|---|---|---|---|
| Introduction to Fusion | Python, Fusion | ||
| Least squares regression | CQO | Python, Fusion | regression, LSE, regularization, lasso, ridge, Huber penalty |
| Small online example | CQO | Python, Fusion | OptServer, regression, online |
| Linear regression techniques | CQO, POW | Python, Fusion | regression, 2-norm, 1-norm, deadzone, p-norm, Czebyshew |
| Stochastic risk measures | LO, EXP, POW | Python, Fusion | portfolio, risk measures, value-at-risk, VaR, CVaR |
| Risk parity portfolio selection | EXP | Python, Fusion | risk parity, portfolio |
| Unit commitment | MICQO | Python, Fusion | unit commitment, production planning |
| SINR Optimization | GP, EXP | Python, Fusion | geometric program, log-sum-exp, signal-to-noise, interference |
| Filter design | SDO | Python, Fusion | trigonometric polynomials, Czebyshev lowpass filter |
| Binary quadratic problems | QP, SDP | Python, Fusion | SDP relaxation, branch and bound, binary QP |
| Subcarrier and power allocation | MIO, EXP | Python, Fusion | power allocation, data rate, channel allocation, F-SPARC |
| Geometric facility location | MICQO | Python, Fusion | planar coverage, wireless network design |
| 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 |
| Exact planar cover | MIO | Python | combinatorial, binary variables, certificate |
| Approximating uncertain inequalities | EXP | Python, Fusion | adjustable robust, approximation, safe region |
| Wasserstein barycenter | LO | Fusion, CVXPY, Pyomo | Wasserstein distance, averaging, barycenter |
| Wasserstein barycenter with regularization | EXP | Fusion, CVXPY | Wasserstein distance, entropy, barycenter, regularization |
| Wasserstein barycenter (Julia) | LO | Julia, JuMP | Wasserstein distance, averaging, barycenter |
| Wasserstein barycenter with regularization (Julia) | EXP | Julia, JuMP | Wasserstein distance, entropy, barycenter, regularization |
| Utility based option pricing | CQO, EXP, POW | Python, Fusion | stochastic process, reservation price, portfolio, option pricing, HARA utility |
| Distributionally robust portfolio | LO | Python, Fusion | stochastic optimization, robust optimization, portfolio, Wasserstein metric |
Publications and Technical Reports
| Title | Assoc. files | Date | Rev. date |
|---|---|---|---|
| Projection onto the exponential cone: a univariate root-finding problem | 12-jan-2021 | ||
| A computational practicability study of MIQCQP reformulations | 08-dec-2020 | 10-dec-2020 | |
| A primal-dual interior-point algorithm for nonsymmetric exponential-cone optimization | 27-may-2019 | 10-mar-2021 | |
| 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 |
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 |
