MOSEK

MOSEK
Developer(s) MOSEK ApS
Stable release
7.1
Development status Active
Type Mathematical optimization
License Proprietary
Website 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 (aka. 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:

MOSEK provides interfaces 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,[4] R,[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. ↑ http://docs.mosek.com/
  5. ↑ https://r-forge.r-project.org/projects/rmosek/ Rmosek
  6. ↑ MOSEK @ Yalmip homepage


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