I've been experimenting with the 'cbc' solver in pyomo, implementing it like this:
import pyomo.environ as pe
solver = pe.SolverFactory('cbc')
result = solver.solve(m)
Currently, I've primarily used the built-in 'glpk' solver that comes with pyomo, but I've noticed that 'cbc' can outperform it in various scenarios.
The tools and versions I'm working with are: Python 3.XX
Anaconda environment
Windows 10
Pyomo (installed via Conda)
Enhancing the capabilities of pyomo by leveraging a more sophisticated solver would be fantastic!