Wednesday, June 23, 2021

MOSEK 9.3 beta, support for linuxaarch64

We have released a beta version of MOSEK 9.3. It is currently only available for download from our website

Release notes:

This version is a direct continuation of 9.2 with no changes to existing interfaces. The new features are:

  • support for Linux on ARM64 (aarch64), including Optimizer API and Fusion API for C/C++,Java,Python,.NET. The interior-point and conic optimizers are single-threaded on that platform.
  • Updated FLEXlm to version 11.18. In particular, floating license users who upgrade clients to MOSEK 9.3 must also upgrade license server binaries (lmgrd) to the ones from the 9.3 MOSEK distribution for compatibility. The new license server is as always backwards compatible.
  • Improved performance when solving many tasks in parallel.

Friday, June 4, 2021

Price increase from October 2021

In February 2020 we announced a price increase, which was later postponed due to the COVID-19 events.

This price increase will now come into effect from October 1st, 2021

Prices go up 5.4% on average: the basic PTS and PTON floating license prices increase by 100 USD each, and the remaining values are adjusted appropriately, following our common rule that a server license is worth 4 times the floating license and that annual maintenance for each part is 25% of the base price for the part. 

New prices can be found at the top of

The current prices remained unchanged since 2015.

Tuesday, April 20, 2021

Data-driven distributionally robust optimization with MOSEK

We posted a video where our very own Utkarsh Detha accompanied by the authors of the award-winning paper  "Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations", Assistant Prof. Peyman Mohajerin Esfahani and Prof. Daniel Kuhn, discuss the work presented in that paper.

We also show how to quickly and easily implement such an approach using our Fusion API for Python. This video focuses on the key new feature: parameters in Fusion. Parametric Fusion allows MOSEK to rapidly resolve a model, and combined with the warm-start capability of the Simplex optimizer, it becomes a powerful tool in every optimizer's garage.

See: the video, our notebook on the same topic, the research paper.