Optimization Without Derivatives: Prima Fortran Version and Inclusion in SciPy

Re:Optimization Without Derivatives: Prima Fortran Version a... by domcoltd on Tuesday May 16, 2023 @11:24AM (#35963112)

Agreed. If (approximate) 1st-order information can be obtained in any way (even by *carefully* deployed finite difference), then gradient-based methods should be used. It is wrong to use DFO in such cases.

> DFOs tend to have issues past a few dozens variables.

It seems that the PRIMA git repo https://github.com/libprima/prima shows results on problems of hundreds of variables. Not sure how to interpret the results.

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Re:Optimization Without Derivatives: Prima Fortran Version a... by domcoltd on Tuesday May 16, 2023 @11:31AM (#35963213)

> DFOs tend to have issues past a few dozens variables.

It is interesting to check the results in section 5.1 of the following paper:

https://arxiv.org/pdf/2302.13246.pdf

where these algorithms are compared with finite-difference CG and BFGS included in SciPy.

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