Commercial Partners

<table class="clean"> <tr> <td><a href=""><img src="/Images/partners/AMPL.jpg"></a></td> <td>AMPL is an algebraic modeling language for formulating optimization problem originally developed at Bell Labratories by Robert Fourer, David M. Gay and Brian W. Kernighan. MOSEK ApS is an authorized reseller of AMPL</td> <tr> <td><a href=""><img src="/Images/partners/CVX.jpg"></td> <td>CVX is an award-winning modeling framework for convex and mixed-integer convex programming. CVX is implemented as a MATLAB toolbox, and model objectives and constraints are specified using natural MATLAB syntax. The surrounding MATLAB environment provides powerful tools for pre-processing of model inputs, post-processing and visualization of results, and building advanced applications. CVX Research, Inc. sells CVX/Mosek bundles as well as licenses to connect CVX to your existing MOSEK installations.</td> <tr> <td><a href=""><img src="/Images/partners/FRONTLINE.jpg"></a></td> <td>The MOSEK Solver takes maximum advantage of the new Polymorphic Spreadsheet Interpreter in Risk Solver Platform and Premium Solver Platform to obtain second partial derivatives of the problem functions (the Hessian matrix) at each major iteration or Trial Solution. On quadratic and SOCP problems, the Hessian matrices are constant -- once they are obtained, the MOSEK Solver is as lightning-fast on these problems as it is on linear programming problems!</td> <tr> <td><a href=""><img src="/Images/partners/GAMS.jpg"></a></td> <td>MOSEK can be used from the algebraic modelling language GAMS to solve linear, qudratic, conic, general convex, and mixed integer optimization problems. For details consult the GAMS website. The GAMS/MOSEK package should be purchased directly from GAMS. For pricing and sales information please contact GAMS.</td> <tr> <td><a href=""><img src="/Images/partners/OPTIRisk.jpg"></a></td> <td>OptiRisk Systems offers an extensive range of software for Optimisation and Risk applications.</td> <tr> <td><a href=""><img src="/Images/partners/REMSOFT.jpg"></a></td> <td>Remsoft provides asset lifecycle optimization solutions that empower executives to maximize the performance and value of land-based and infrastructure assets. Through advanced analytics, modeling and spatial planning technology, Remsoft simplifies complex, high-variable decisions to fuel long-term sustainability.</td> </table>

Non-commercial Partners

<table class="clean"> <tr> <td><a href=""><img src="/Images/partners/COIN-OR.jpg"></a></td> <td>Open Solver Interface (Osi) provides an abstract base class to a generic linear programming (LP) solver, along with derived classes for specific solvers. Osi is written in C++ and is released as open source code as part of the COIN-OR initiative.</td> <tr> <td><a href=""><img src="/Images/partners/yalmip.jpg"></a></td> <td>YALMIP is a language for advanced modeling and solution of convex and nonconvex optimization problems. It is implemented as a free (as in no charge) toolbox for MATLAB. YALMIP focuses on the language and the higher level algorithms, while relying on external solvers such as MOSEK for computation. YALMIP was developed by Johan Lofberg.</td> <tr> <td><a href=""><img src="/Images/partners/rome.jpg"></a></td> <td>ROME is an algebraic modeling language designed to solve a class of robust optimization problems. ROME runs in the MATLAB environment, so that users can take full advantage of the numerical and graphical capabilites of MATLAB for preprocessing and analysis of data.</td> <tr> <td><a href=""><img src="/Images/partners/I2C2Grey_small.png"></a></td> <td>OPTimization Interface (OPTI) Toolbox is a free MATLAB toolbox for constructing and solving linear, nonlinear, continuous and discrete optimization problems. A range of open source and academic solvers are supplied for the Windows user - no compilation required!</td> <tr> <td><a href=""><img src="/Images/partners/juliaoptlogo.png"></a></td> <td>JuliaOpt is a collection of open-source optimization-related packages in Julia, a technical computing language that aims to combine MATLAB's productivity and C's performance. JuliaOpt includes two modeling languages, JuMP and Convex.jl with support for linear, mixed-integer, conic, and nonlinear optimization along with a low-level direct interface to Mosek.</td> </table>