I am new to pyomo, so this is a basic question about the capabilities/restrictions of pyomo as a whole. I have read most of the “Optimization Modeling in Python” textbook about using pyomo, and I believe that pyomo would be a great tool for me to use for a modeling project I am currently working on. However, I do have one concern. In many equations in my model, I need to access a Fortran library linked through a DLL (it’s a commercial equation of state). The functions in this Fortran library are very non-linear. From what I understand, non-linear pyomo equations must be represented through the non-linear functions provided from the pyomo library. Is there any way to use pyomo while using this DLL, or would I need to rebuild all of the functions in the Fortran library in python with pyomo functions?

I’m using Python 3.12.3 and Pyomo 6.7.0, and I use VSCode as my code editor. I have already connected GAMS 25.1 to Python. Now, I want to add GAMS 24.1 to Python. Here are my questions:

Does pyomo support to pass a function to access model value each iteration? I want to check the solution every 50 iter, how can I achieve this?

Does pyomo support to pass a function to access model value each iteration? I want to check the solution every 50 iter, how can I achieve this?

recently I have been trying to solve the optimization problem in the paper named
‘System-level analysis of lignin valorization in lignocellulosic biorefineries’
using Pyomo. But the three constraints conflicts each other, which not happened before using GAMS.
I have revisited all the data and codes, but it is totally same with what I did by GAMS.
Therefore, I’m wondering if there is an inherent difference btw GAMS and Pyomo when it comes to dealing with constraints.
Can you guys help me, please?

I want to utilize pyomo to solve 2stage stochastic programs (achieved from SIPLIB, which is in smps format), but how to make the smps file compatible with pyomo?

By default, variables seem to be initialized in Pyomo. Then the solver uses this initial point. Is there a way to not initialize variables in Pyomo and let the solver compute the initial point? I tried to initialized to None but an initial point is still passed to the solver

Given this set and constraint definition

I’m using a _rule_function to build constraints.
Constraint(model.S, model.T, model.sc, rule=_rule_function, doc=’RestrictionX’)