SIsidereus·Nov 27, 2017
We compared our OSQP solver to other general-purpose solvers. That's why we chose GUROBI and Mosek. There are also examples of control problems for which it is possible to design very efficient tailored methods. However our point is not to compare our solver to specific methods for certain classes (like libsvm).
In the benchmarks we are comparing examples with randomly generated data because we were interested in ~1400 problems in a range from 100 to 10 million nonzeros. The examples are not just random QPs, but data are generated in a reasonable manner and they have the same structure as problems people would actually solve in practice. In the arXiv paper we described in detail how we generated and checked optimality for the examples.
As mentioned in the README of the repository that you checked out (https://github.com/oxfordcontrol/osqp
Read the rest
_benchmarks) we used the conversion scripts from here: https://github.com/YimingYAN/QP-Test-Problems
If you know better ways to convert the Maros problems (or other QP/LP benchmarks) to mat files or other formats compatible with Python, please let me know. I would be happy to try them.