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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