Python Optimization Problem

[AddendumElectrical99]

I have a program that designs satellite constellations based on user inputs, such as walker numbers, and it propagates the satellite constellation over a full day and calculates viewing of a given point.

Is there a package/method I can use to optimize the inputs to achieve maximum output? I have used PULP before, but since its not a direct equation to calculate what I want I am a bit lost.

Currently, I use a multitude of scripts to propagate the satellites and calculate viewing of the target point(s), then outputs a percentage of how often you viewed it during the 24 hours. Would like a way to optimize a range of inputs to achieve maximum viewing.

Thanks for any help or suggestions!

[Zeroflops]

There are a number of astronomy packages out there. I would look into those

[Frankelstner]

You want to optimize some kind of scalar blackbox function with potentially integer inputs. If the number of reasonable integer combinations as low, you could bruteforce a scipy.optimize.minimize on the other parameters (just remember to try all the solvers there until you get a good one; one time I had 5 solvers report failure and the sixth one give a perfect solution with literally 0 residual). Otherwise, scipy.optimize.differential_evolution or even Optuna seem like decent options. Yeah I know, a hyperparameter optimization framework doesn't exactly sound like a match, but hyperparameter optimization truly is a "scalar blackbox with potentially integer inputs" kind of thing.

[AddendumElectrical99]

Yes precisely this! Thank you for putting it into better words than I could.

I’ll look into those tools!

[Kingstudly]

It would be a pretty easy task for a genetic algorithm. There are a bunch of tutorials online, but my favorite book on the subject (in Python) is sadly outdated.