Machine learning in Julia Meetup

On Monday, November 20, 2017 we are hosting a meetup organized by JuliaCPH with the topic of Machine Learning in Julia. Enthusiasts of Julia, machine learning and optimization are welcome! For details see

https://www.meetup.com/JuliaCPH/events/244410284/?a=socialmedia

MOSEK 8.1 is out

We are releasing MOSEK 8.1, an improved continuation of version 8.0.

Its main features are:

• Much faster implementation of the Python Fusion API. Depending on the use case the overhead of Fusion is reduced by a factor of 3-10 on large models.
• Introduced C++ Fusion API for 64bit Windows, at least for Microsoft Visual Studio 2015+.
• Performance improvements in the conic optimizer and presolve. Particularly for problems with many dense columns.
• Improved documentation for the Optimizer, Fusion and API reference. 

All interfaces are identical to that of 8.0, meaning a seamless update.

Platform support changes:

• Introduced C++ Fusion for 64bit Windows.
• Dropped support for Python 3.4.
• Dropped the AMPL shell in 32bit Windows.

Quick links:

• Download
• "conda install -c mosek mosek" if using conda installation
• Documentation
• Release notes
• Free trial license
• Free academic license

MOSEK 8.1 beta

We are releasing a beta version of MOSEK 8.1. It is available for download from a separate page

https://mosek.com/resources/downloads/beta/beta

We expect it to replace the main branch 8.0 after a few months of testing. 

The API of version 8.1 is identical with 8.0, but there are other major upgrades:

• Much faster implementation of the Python Fusion API. Depending on the use case the overhead of Fusion is reduced by a factor of 3-10 on large models.
• C++ Fusion API is now available also for Windows, at least for Microsoft Visual Studio 2015 and newer. (Currently only 64bit; the 32bit version is in preparation)
• Some performance improvements in the conic optimizer. Particularly for problems with many dense columns.
• Much improved documentation for the Optimizer, Fusion and API reference. 

Biggest conic quadratic problem solved by MOSEK ever

Recently we got a bug report from a customer. The reason for the bug was that the problem has more than 2^31 nonzeros in the A matrix so a 32 bit integer overflow triggered an assert.

After fixing the bug the problem was not solvable on the largest computer which we had access to. After buying a new DELL PowerEdge R730 server with 2 Xeon E5-2687W v4 3.0GHZ  and 512GB the problem solved in about 2000 seconds using 24 threads using the latest MOSEK version 8.0.0.74.

Here are the size details about the problem:

• Number linear constraints: 140623
• Number of variables: 545634
• Number conic constraints: 124801
• Number of nonzeros in A: 2208749451 (>2^31)
• Number of flops per iteration: 10^13

Because the bug discussed above is present in all previous versions of MOSEK then this is the biggest problem in terms of A nonzeros solved by MOSEK ever.

Easter holidays 2017

Our support and sales will be closed for Easter holidays from and including Thursday, April 13th until and including Monday, April 17th. We resume on Tuesday, April 18th.

Wishing everyone a good Easter,
The MOSEK team

DTU Power Systems and Electricity Markets School 2017

On June 12-16 the The Energy Analytics and Markets Group at the Technical University of Denmark (DTU) is hosting a Summer School Modern Challenges in Power System Operation and Electricity Markets: An Optimization Perspective. This is the second DTU summer school on the topic of electricity markets and power systems, and as before it will have outstanding speakers.

We are very happy to be one of the sponsors of the school. In particular, two MOSEK scholarships are waiting for two outstanding student participants.

Registration is open until May 7th. We hope to see you at the school in June!

Power flow problems - workshop summary

On February 28th we held the Workshop on Semidefinite Optimization in Power Flow problems.

• Spyros Chatzivasileiadis gave a talk about SDO methods for producing stability certificates for power systems and about the optimal power flow under uncertainty.
• Cédric Josz introduced the complex variant of the Lasserre moment hierarchy and discussed the possible advantages of a convex optimizer working directly over the complex numbers.
• Martin Skovgaard Andersen talked about numerical aspects and experiments with convex relaxations of optimal flow problems. In particular, he was able to solve the SDP relaxations of test cases with over 10K power buses using MOSEK.

The slides from all three talks can be found on our website.

We thank the speakers and the participants for making this a great workshop!

MOSEK Team