Matches in DBpedia 2016-04 for { ?s ?p "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.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 to the C, C#, Java and Python languages. Most major modeling systems are made compatible for MOSEK, examples are: AIMMS, AMPL, and GAMS.MOSEK can also be used from popular tools such as matlab, R, CVX, and YALMIP."@en }
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- MOSEK abstract "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.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 to the C, C#, Java and Python languages. Most major modeling systems are made compatible for MOSEK, examples are: AIMMS, AMPL, and GAMS.MOSEK can also be used from popular tools such as matlab, R, CVX, and YALMIP.".
- Q6717127 abstract "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.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 to the C, C#, Java and Python languages. Most major modeling systems are made compatible for MOSEK, examples are: AIMMS, AMPL, and GAMS.MOSEK can also be used from popular tools such as matlab, R, CVX, and YALMIP.".