[Ipopt] Strategies for solving a large scale optimisation problem?

[Omid Bidar]

Dear all,

I'm a new user of IPOPT, trying to solve an optimisation problem in a CFD
context. The number of design variables in the problem is the same as the
number of mesh cells, which are at least 10k but could be up to 500k for
the problems we are working on. So the problem at hand is very nonlinear
and highly dimensional.

A colleague has run the optimisation for a toy problem we're working on
using SNOPT successfully, but it requires a user license. We're looking
into using IPOPT as a free alternative. We've managed to use IPOPT with a
small number of design variables with MUMPS as the linear solver, but the
same setup for large design variables currently takes too long to compute
(we've had to terminate the computation after running it overnight to solve
the problem).

Having looked on the internet I know that people have implemented IPOPT for
very large problems, but I haven't managed to really find any good resource
on how to go about setting up the problem. Can someone please advise?

For brevity's sake I've not included a lot of details about the problem but
can share more details should this be required.

Cheers,
Omid
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