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u/Opt4Deck

▲ 7 r/optimization+1 crossposts

>This post presents the use of the Adjoint method for parameter estimation in an R–L circuit.

Hi everyone! 👋

Lately, I have been exploring the possibilities of the Adjoint Method in optimization! Specifically, the above example uses the method to estimate two parameters and I wanted to share it with the community.

I’m solving a parameter estimation problem in an R–L circuit, where the goal is to recover source frequency (ω) and phase (φ) by minimizing the error between fitting and aim curves.

What struck me is how efficient gradient-based approaches are in such well-defined physical problems, especially compared to "black-box" tools that require much more evaluations.

I was also excited by the fact that the method guarantees the smallest possible number of calls to the objective function to calculate the gradient-vector, regardless of the number of variables! 🚀

Questions:

  • Does anyone have experience with Adjoint vs other sensitivity analysis methods?
  • Does anyone want the mathematical proof of the method?

P.S.: I'd be happy to share the code and notes if anyone’s interested.! ✍️

u/Opt4Deck — 9 days ago
▲ 2 r/optimization+1 crossposts

I have a question about genetic algorithms in practice.

As far as I understand, they have the advantage of not needing derivatives and not getting stuck easily in local maximum/minimum, but they are relatively slow due to the large number of evaluations.

I wonder if anyone has tried using a neural network in parallel, so that after a certain point it “filters” candidate solutions before they are properly evaluated.

In other words, something like a surrogate model that learns which solutions are worth considering.

Has anyone worked on something like this in practice? Does it really help or does it end up making things more complicated?

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u/Opt4Deck — 11 days ago
▲ 1 r/learnmachinelearning

I've started looking into optimization methods (Simplex, BFGS, Genetic Algorithms, etc.) and I'm trying to understand when it makes sense to use each one.

I feel like many people use them as black-boxes without knowing what's going on behind the scenes.

Those of you with experience: how do you choose a method in practice? And how important is it to understand the algorithm "from the inside"?

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u/Opt4Deck — 12 days ago