u/CryptographerAny4589

Hello everyone!

I'm looking for resources on optimization algorithms for black-box objective functions that are expensive to evaluate.

In my case, a single evaluation takes about 6 hours because it involves an FEA simulation. I also have access to a cluster, so I can run 3–5 evaluations simultaneously.

I have already tried Bayesian optimization and obtained good results, but I wonder whether there are other good alternatives, especially for cases where several trial points can be evaluated in parallel.