MOSEK

MOSEK
Developer(s) MOSEK ApS
Stable release
8.1.0.x
Type Mathematical optimization
License Proprietary
Website www.mosek.com

MOSEK is a software package for the solution of linear, mixed-integer linear, quadratic, mixed-integer quadratic, quadratically constraint, conic and convex nonlinear mathematical optimization problems. The emphasis in MOSEK is on solving large scale sparse problems. Particularly the interior-point optimizer for linear, conic quadratic (a.k.a. Second-order cone programming) and semi-definite (aka. semidefinite programming) problems is very efficient. A special feature of the MOSEK interior-point optimizer is that it is based on the so-called homogeneous model which implies MOSEK can reliably detect a primal and/or dual infeasible status as documented in several published papers.[1][2][3]

In addition to the interior-point optimizer MOSEK includes:

  • Primal and dual simplex optimizer for linear problems.
  • A primal network simplex optimizer for problems with special network structure.
  • Mixed-integer optimizer for linear, quadratic and conic quadratic problems.

MOSEK provides interfaces[4] to the C, C#, Java and Python languages. Most major modeling systems are made compatible for MOSEK, examples are: AMPL, and GAMS. MOSEK can also be used from popular tools such as MATLAB, R (an outdated version of package Rmosek is available from the CRAN server, the up-to-date version is provided by Mosek ApS[5]), CVX, and YALMIP.[6]

References

  1. ↑ E. D. Andersen and Y. Ye. A computational study of the homogeneous algorithm for large-scale convex optimization. Computational Optimization and Applications, 10:243–269, 1998
  2. ↑ E. D. Andersen and K. D. Andersen. The MOSEK interior point optimizer for linear programming: an implementation of the homogeneous algorithm.In H. Frenk, K. Roos, T. Terlaky, and S. Zhang, editors, High Performance Optimization, pages 197–232. Kluwer Academic Publishers, 2000
  3. ↑ E. D. Andersen, C. Roos, and T. Terlaky. On implementing a primal-dual interior-point method for conic quadratic optimization. Math. Programming, 95(2), February 2003
  4. ↑ https://www.mosek.com/documentation/
  5. ↑ http://docs.mosek.com/8.1/rmosek/index.html
  6. ↑ MOSEK @ Yalmip homepage



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