Source code for pyomo.contrib.preprocessing.plugins.remove_zero_terms

#  ___________________________________________________________________________
#
#  Pyomo: Python Optimization Modeling Objects
#  Copyright (c) 2008-2024
#  National Technology and Engineering Solutions of Sandia, LLC
#  Under the terms of Contract DE-NA0003525 with National Technology and
#  Engineering Solutions of Sandia, LLC, the U.S. Government retains certain
#  rights in this software.
#  This software is distributed under the 3-clause BSD License.
#  ___________________________________________________________________________

# -*- coding: UTF-8 -*-
"""Transformation to remove zero terms from constraints."""


from pyomo.core import quicksum
from pyomo.core.base.constraint import Constraint
from pyomo.core.base.transformation import TransformationFactory
import pyomo.core.expr as EXPR
from pyomo.core.plugins.transform.hierarchy import IsomorphicTransformation
from pyomo.repn import generate_standard_repn
from pyomo.common.config import ConfigDict, ConfigValue


[docs]@TransformationFactory.register( 'contrib.remove_zero_terms', doc="Remove terms 0 * var in constraints" ) class RemoveZeroTerms(IsomorphicTransformation): """Looks for :math:`0 v` in a constraint and removes it. Currently limited to processing linear constraints of the form :math:`x_1 = 0 x_3`, occurring as a result of fixing :math:`x_2 = 0`. .. note:: TODO: support nonlinear expressions """ CONFIG = ConfigDict("RemoveZeroTerms") CONFIG.declare( "constraints_modified", ConfigValue( default={}, description="A dictionary that maps the constraints modified during " "the transformation to a tuple: (original_expr, modified_expr)", ), ) def _apply_to(self, model, **kwargs): """Apply the transformation.""" config = self.CONFIG(kwargs) m = model for constr in m.component_data_objects( ctype=Constraint, active=True, descend_into=True ): repn = generate_standard_repn(constr.body) if not repn.is_linear() or repn.is_constant(): continue # we currently only process linear constraints, and we # assume that trivial constraints have already been # deactivated or will be deactivated in a different # step original_expr = constr.expr # get the index of all nonzero coefficient variables nonzero_vars_indx = [ i for i, _ in enumerate(repn.linear_vars) if not repn.linear_coefs[i] == 0 ] const = repn.constant # reconstitute the constraint, including only variable terms with # nonzero coefficients constr_body = ( quicksum( repn.linear_coefs[i] * repn.linear_vars[i] for i in nonzero_vars_indx ) + const ) if constr.equality: new_expr = constr_body == constr.upper elif constr.has_lb() and not constr.has_ub(): new_expr = constr_body >= constr.lower elif constr.has_ub() and not constr.has_lb(): new_expr = constr_body <= constr.upper else: # constraint is a bounded inequality of form a <= x <= b. new_expr = EXPR.inequality(constr.lower, constr_body, constr.upper) constr.set_value(new_expr) config.constraints_modified[constr] = (original_expr, new_expr)