I’ve read this series if articles about using Excel Solver for all kinds of optimization problems. This is very neat, but of course, I would prefer to write models with code instead, preferably in D. I glanced at mir-optim but it requires knowledge of advanced math. Is there something more approachable for a layperson?

On Sunday, 1 January 2023 at 21:11:06 UTC, Ogi wrote:

What do you want to optimize? Optimization in general requires reasonably advanced mathematics, whereas a single problem can be simplified.

On Sunday, 1 January 2023 at 21:11:06 UTC, Ogi wrote:

Maybe mir-optim and dopt are the only options.
You can check JuMP (Julia package and resources). Maybe port some of them to D will be the start of new optim solver package. But in general behind the optimisation problems always lying math..

On Sunday, 1 January 2023 at 22:00:29 UTC, max haughton wrote:

There are a lot of C libraries too that you can call from D for optimization too, but like Max says knowing what you want to optimize helps a lot. Excel’s optimizer works for small problems but chokes if the dimension increases too much.It is probably some sort of nonlinear gradient free solver.

On Tuesday, 3 January 2023 at 21:13:55 UTC, Sergey wrote:

I have a wrapper for the R optimization libraries somewhere. It lets you call the same C libraries underlying R's optim, with the option to choose the algorithm. Haven't used it in a while, but as I recall it was pretty easy to use. I probably also wrapped some of the third-party R optimization libraries at some point.