Here's a colab notebook that will recommend a black-box optimizer for your objective function.
The recommendations are based on the Elo ratings for derivative-free optimization packages (see https://lnkd.in/ghgmKfN) which are now quite mature.
The notebook will also compare directly the performance of many different optimization strategies, drawn from disparate libraries, on your objective function(s).
This is a lot faster than trying out nlopt, bobyqa, dlib, nevergrad, pysot, hebo, bayesopt, skopt, ax-platform, shgo, pymoo, hyperopt, optuna, platypus, ultraopt and other Python packages, not to mention variations within, yourself.
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The notebook will also compare directly the performance of many different optimization strategies, drawn from disparate libraries, on your objective function(s).
This is a lot faster than trying out nlopt, bobyqa, dlib, nevergrad, pysot, hebo, bayesopt, skopt, ax-platform, shgo, pymoo, hyperopt, optuna, platypus, ultraopt and other Python packages, not to mention variations within, yourself.
A lot faster.