Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating, solving, and analyzing optimization models.
SciPy is an open source library of algorithms and mathematical tools for the Python programming language.
Pyomo runs in less than one minute and scipy takes 4 hours
Why do IPOPT and Scipy bring different results using the same inputs, constraints and objective function?
Modeling in pyomo is much faster than in scipy but pyomo documentation does not seem to say explicitly if this is feasible
Call scipy.optimize inside pyomo