The MOSEK optimization software is designed to solve large-scale mathematical optimization problems. MOSEK main features are listed below. For additional questions, contact our support or browse the online documentation.
Problem types MOSEK can solve
- Conic quadratic.
- Conic with exponential and power cone.
- Semi-definite (Positive semi-definite matrix variables).
- Convex quadratic and quadratically constrained.
- Mixed integer linear, conic and quadratic.
- Problem size limited only by the available memory.
- Primal and dual simplex optimizers for linear programming.
- Highly efficient pre-solver for reducing problem size before optimization.
- Branch&bound&cut algorithm for mixed integer problems.
Strengths and features of MOSEK
- The strongest point of MOSEK is its state-of-the-art interior-point optimizer for continuous linear, quadratic and conic problems.
- Exploits hardware i.e. SSE2 instructions available in recent Intel CPUs.
- The optimizer is parallelized and capable of exploiting multiple CPUs/cores.
- The optimizer is run-to-run deterministic.
- Reads and writes industry standard formats such as the MPS, CBF and LP formats.
- Includes tools for infeasibility diagnosis, repair and sensitivity analysis for linear problems.
- Ships with an optimization server for remote optimization.
InterfacesSee supported platforms for details.
- Optimizer API: C, Java, .NET, Python.
- Fusion API: C++, Java, .NET, Python.
- MOSEK optimization toolbox for MATLAB.
- R package.
- Command line interface.
- Other third party commercial and open-source tools and products have interfaces to MOSEK.
- Supported platforms: OSX, Windows, Linux
- MOSEK can not solve nonconvex problems. Only convex problems including one or more integer constrained variables.
- MOSEK has no sequential quadratic optimizer because it is not competitive with the algorithms implemented in MOSEK.
Try MOSEK today!
Request your free license in the Trial License page. For information on pricing and how to order please see the sales page.