The OPAL Discussion Forum

["Snuverink Jochem (PSI)" <jochem.snuverink AT psi.ch>]

Dear Renato,

Did you verify that the solutions you found with the surrogate model are also solutions with OPAL? (That is run the OPAL-simulation with that input and verify that it fulfils all constraints).

If that indeed works, then I would suggest to try to reduce the bounds more, or perhaps fix some input variables. 

You have a 9 dimensional input space with 81 constraints, and it might be that the valid region is very small compared to the input space such that even 7500 individuals are not enough.

The optimiser is not optimised to find the first generation quickly. There is an optimizer flag called `INITIAL_OPTIMIZATION`, if you set this to TRUE (default FALSE), it will speed up the first generation. It is mostly for finding the last feasible individuals, so it will probably not help in your case.

What you can also do is generate the feasible solutions with the surrogate model, make a JSON generation file from them, and start the optimisation with that generation (`STARTPOPULATION`).

Hope that helps,

Jochem

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From: opal-request AT lists.psi.ch <opal-request AT lists.psi.ch> on behalf of Renato Bellotti <renato.bellotti AT psi.ch>
Sent: Tuesday, May 5, 2020 4:10 PM
To: opal AT lists.psi.ch
Subject: [Opal] Optimiser

 

Dear OPAL developers,

I am experiencing problems with the optimiser. I am trying to solve the following problem:

You can see that I try to restrict the beam size within the first 10m of the accelerator.

Unfortunately, the optimiser does not find a single feasible individual, although it has tried > 7500 configurations.

I know that the problem has solutions that fulfil the constraint: Thanks to an ML surrogate model, I was able to run the optimisation with the pymoo Python library.

I am now a bit at a loss that OPAL cannot solve the problem while the Python library can. Am I doing something wrong in the config file (see appendix)?

I'm looking forward to your answers,

Renato