Gradient Free Optimizers: A collection of modern optimization methods in Python

Re:Gradient Free Optimizers: A collection of modern optimiza... by simonblanke on Sunday February 28, 2021 @09:48AM (#26293738)

I am currently working on the Nelder-Mead optimiser. I will also look into "BOBYQA". I am always searching for interesting algorithms that my users need. If you have more suggestions you can open an issue in the repository.

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Re:Gradient Free Optimizers: A collection of modern optimiza... by sleavey on Sunday February 28, 2021 @12:19PM (#26294932)

I've used this, and it works nicely: https://github.com/numericalalgorithmsgroup/pybobyqa. I'd be happy if it were added to your project, then I could just use yours and have access to a bunch of alternatives with the same API.

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Re:Gradient Free Optimizers: A collection of modern optimiza... by twic on Sunday February 28, 2021 @10:17AM (#26293933)

That's good to hear. I don't have any other specific requests - for me it seems impossible to know what will work on my problems, so i just try things at random to see what works!

I don't know the architecture of your project, but is there any way it could include NLopt, and so make all of its algorithms available? Some of them could be useful, and i doubt it's a good use of your time to reimplement them all from scratch.

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Re:Gradient Free Optimizers: A collection of modern optimiza... by simonblanke on Monday March 01, 2021 @04:59AM (#26301204)

Unfortunately NLopt cannot be included into Gradient-Free-Optimizers. But i would like to implement multiple algorithms that are also preset in NLopt.

I think it will help my understanding of optimization algorithms if i implement them myself. I currently have my eyes on the Downhill-simplex, Direct and Powell's Method. But they are quite different from what i have already implemented, so this could take some time.

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