ScaleModel

(class from pyomo.core.plugins.transform.scaling)

class pyomo.core.plugins.transform.scaling.ScaleModel(**kwds)[source]

Bases: Transformation

Transformation to scale a model.

This plugin performs variable, constraint, and objective scaling on a model based on the scaling factors in the suffix ‘scaling_factor’ set for the variables, constraints, and/or objective. This is typically done to scale the problem for improved numerical properties.

Supported transformation methods:

apply_to
create_using
propagate_solution

By default, scaling components are renamed with the prefix scaled_. To disable this behavior and scale variables in-place (or keep the same names in a new model), use the rename=False argument to apply_to or create_using.

Examples

>>> from pyomo.environ import *
>>> # create the model
>>> model = ConcreteModel()
>>> model.x = Var(bounds=(-5, 5), initialize=1.0)
>>> model.y = Var(bounds=(0, 1), initialize=1.0)
>>> model.obj = Objective(expr=1e8*model.x + 1e6*model.y)
>>> model.con = Constraint(expr=model.x + model.y == 1.0)
>>> # create the scaling factors
>>> model.scaling_factor = Suffix(direction=Suffix.EXPORT)
>>> model.scaling_factor[model.obj] = 1e-6 # scale the objective
>>> model.scaling_factor[model.con] = 2.0  # scale the constraint
>>> model.scaling_factor[model.x] = 0.2    # scale the x variable
>>> # transform the model
>>> scaled_model = TransformationFactory('core.scale_model').create_using(model)
>>> # print the value of the objective function to show scaling has occurred
>>> print(value(model.x))
1.0
>>> print(value(scaled_model.scaled_x))
0.2
>>> print(value(scaled_model.scaled_x.lb))
-1.0
>>> print(value(model.obj))
101000000.0
>>> print(value(scaled_model.scaled_obj))
101.0

__init__(**kwds)[source]

Methods

`__init__`(**kwds)
`apply`(model, **kwds)	DEPRECATED.
`apply_to`(model, **kwds)	Apply the transformation to the given model.
`create_using`(model, **kwds)	Create a new model with this transformation
`propagate_solution`(scaled_model, original_model)	This method takes the solution in scaled_model and maps it back to the original model.

Member Documentation

apply(model, **kwds): DEPRECATED.

Deprecated since version 4.3.11323: Transformation.apply() has been deprecated. Please use either Transformation.apply_to() for in-place transformations or Transformation.create_using() for transformations that create a new, independent transformed model instance.

apply_to(model, **kwds): Apply the transformation to the given model.

create_using(model, **kwds): Create a new model with this transformation

propagate_solution(scaled_model, original_model)[source]

This method takes the solution in scaled_model and maps it back to the original model.

It will also transform duals and reduced costs if the suffixes ‘dual’ and/or ‘rc’ are present. The scaled_model argument must be a model that was already scaled using this transformation as it expects data from the transformation to perform the back mapping.

Parameters:

scaled_model (Pyomo Model) – The model that was previously scaled with this transformation
original_model (Pyomo Model) – The original unscaled source model