MOSEK is a tool for solving mathematical optimization problems such as: linear programs, quadratic programs, conic problems, mixed integer problems.
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
- Semidefinite (Positive semidefinite matrix variables)
- Quadratic and quadratically constrained
- General convex nonlinear
- Mixed integer linear, conic and quadratic
- Problem size limited only by the available memory.
- Interior-point optimizer with basis identification.
- Primal and dual simplex optimizers for linear programming.
- Highly efficient presolver for reducing problem size before optimization.
- Network-simplex for problems with network flow structure.
- Branch&bound&cut algorithm for mixed integer problems.
Strengths of MOSEK
The strong point of MOSEK is its state-of-the-art interior-point optimizer for continous linear, quadratic and conic problems.
The interior-point optimizer is capable of exploiting multiple CPUs/cores. A concurrent optimizer is available that makes it possible to solve one problem with different optimizers simultaneously. The default mixed integer optimizer is parallelized and is run-to-run deterministic.
Other features of MOSEK
Reads and writes industry standard formats such as the MPS and LP formats. Includes tools for infeasibility diagnosis and repair. Sensitivity analysis for linear problems.
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