The MOSEK Optimization Software is designed to solve large-scale mathematical optimization problems. MOSEK provides specialized solvers for linear programming, mixed integer programming and many types of nonlinear convex optimization problems.
Problem types MOSEK can solve:
 * Linear problems.
 * Conic quadratic problems.
 * Quadratic and quadratically constrained problems.
 * General convex nonlinear problems.
 * Mixed integer linear, conic and quadratic problems.

Technical highlights of MOSEK are:
 * Problem size is only limited by the available memory.
 * An interior-point optimizer with basis identification.
 * Both primal and dual simplex optimizers for linear programming.
 * Highly efficient presolve for reducing problem size before optimization.
 * A special optimizer is available for problems with network flow structure.
 * For mixed integer problems MOSEK implements a branch & bound & cut algorithm.
Parallel capabilities:
 * 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.

Other features of MOSEK:
 * Reads and writes industry standard formats such as MPS, LP and XML.
 * Includes tools for infeasibility diagnosis and repair.
 * Sensitivity analysis for linear problems.

MOSEK version 7.0.0.85
The new version includes important performance enhancements and bug fixes. The major changes are:
 Improved the dense column detection.
 Improved the presolve to handle a numerical bad case related to doubleton equations better.
 Fixed a bug that made Java, .NET and Python optimizer APIs which caused a crash in special cases.
 Fixed a bug in the put solution slice functions that occurred if no solution was previously defined.
 Employ a newer version of the Intel C compiler tool chain.
 Special characters are now allowed in license paths on Windows.
 Fixed a bug that made the interior-point optimizer crash in certain extremely rare cases.
 Updated the toolbox manual.

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