I was able to speed up my solver significantly using the following recommendations from the documentation:
If you have a convex problem, or if you don't know whether your problem is convex, use interior-point-convex. If you have only bounds, or only linear equalities, use trust-region-reflective. If you have a nonconvex problem that does not satisfy the restrictions of trust-region-reflective, use active-set.
"Min " <firstname.lastname@example.org> wrote in message <email@example.com>... > Hi Johan, > > Clpmex seems to need a license. Therefore, bpmpdmex might be the only free option for large-scale sparse QP problems. > However, the bpmpdmex that I downloaded only has a pre-compiled 32bit linux version. > Do you know how to compile bpmpdmex for a 64bit linux machine? The reason I can'y compile it is because I do not find the source code of bpmpd and any documents on using bpmpdlib. > > Best, > -MS > > > "Johan L?fberg" <firstname.lastname@example.org> wrote in message <email@example.com>... > > "hicham bouchnaif" <firstname.lastname@example.org> wrote in message > > <email@example.com>... > > > > > > > The alternatives are interfaced to MATLAB, or do you mean > > > > that you won't accept mex? > > > > > > no it's just a matter of accuracy, I ll try this OOQP stuff > > > and see how it works. > > > > > > Regards > > > > > > > > > > Correct, QPC is not applicable due to sparsity. clpmex > > should work straight out of the box, so will bpmpdmex. I > > think I had problems obtaining compiled versions of ooqp > > last time I tried.