generate_norm2sq_objective_function
(function from pyomo.contrib.mindtpy.util)
- pyomo.contrib.mindtpy.util.generate_norm2sq_objective_function(model, setpoint_model, discrete_only=False)[source]
This function generates objective (FP-NLP subproblem) for minimum euclidean distance to setpoint_model.
L2 distance of \((x,y) = \sqrt{\sum_i (x_i - y_i)^2}\).
- Parameters:
model (Pyomo model) – The model that needs new objective function.
setpoint_model (Pyomo model) – The model that provides the base point for us to calculate the distance.
discrete_only (bool, optional) – Whether to only optimize on distance between the discrete variables, by default False.
- Returns:
The norm2 square objective function.
- Return type: