add_var_bound

(function from pyomo.contrib.mindtpy.util)

pyomo.contrib.mindtpy.util.add_var_bound(model, config)[source]

This function will add bounds for variables in nonlinear constraints if they are not bounded.

This is to avoid an unbounded main problem in the LP/NLP algorithm. Thus, the model will be updated to include bounds for the unbounded variables in nonlinear constraints.

Parameters:

  • model (PyomoModel) – Target model to add bound for its variables.

  • config (ConfigBlock) – The specific configurations for MindtPy.