MOSEK

MOSEK is a high-performance mathematical optimization software package and solver developed by MOSEK AB. It focuses on convex optimization and conic programming, including linear programming, quadratic programming, second-order cone programming, and semidefinite programming. The solver is designed to handle large-scale problems and is used across finance, engineering, energy, and research to model and solve complex optimization tasks.

MOSEK provides programming interfaces for multiple languages, including C, C++, Java, .NET, MATLAB, Python, and R. It can be used directly via its APIs or integrated with various modeling environments and tools through those interfaces. The software emphasizes robustness, numerical stability, and scalability, incorporating interior-point methods and optimized linear algebra routines. It also supports features such as warm starts and parallel execution to improve performance on large problems.

MOSEK is distributed under commercial licenses, with options for academic licenses and trial evaluations. It runs on Windows, Linux, and macOS and can be embedded in applications or accessed remotely via its APIs. Typical applications include portfolio optimization, risk management, engineering design, control, and machine learning tasks that can be formulated as LPs, QPs, SDPs, and related convex optimization problems. The product is known for its combination of speed, reliability, and broad language support, making it a common choice for both enterprise deployments and research workflows.