[Python] Is there a python framework for metaheuristic solvers that accepts optimization...

I am looking for a Python framework that allows me to apply metaheuristic solvers to optimization problems. I build my optimization problems using pyomo. For example I found pymoo which sounds quite promising (as it already has some metaheuristic solvers like genetic algorithm implemented).

HOWEVER: In all the examples or tutorials I could find, they only use up to 2 or 3 Variables and 2 or 3 constraints. Which is fine in case of those tutorials, this can easily be hard coded. But I have optimization problems consisting easily of 10.000 or 100.000 and more variables and constraints (and I use pyomo to conveniently formulate those optimization problems programmatically). It won't be feasible to type down all those lengthy constraints (even the objective function alone would be too long to type down, and probably I would make hundreds of typos).

So my question is: Is there some kind of interface from pyomo to pymoo, which allows me to directly use the pyomo optimization problem as the pymoo problem? Or maybe any other alternative frameworks (but I would like to stick with pyomo, as I am already used to it)?

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