def _tighten_bounds(self):
self.range_reduction_model_setup()
assert self._best_objective != self.unbounded_objective()
# setup objective
assert self.problem.pyomo_model_objective.active
self.problem.pyomo_model_objective.deactivate()
tmp_objective = pmo.objective()
tmp_objective_name = add_tmp_component(self.problem.pyomo_model,
"rr_objective", tmp_objective)
# setup optimality bound if necessary
tmp_optbound_name = None
tmp_optbound = None
if self._best_objective != self.infeasible_objective():
tmp_optbound = create_optimality_bound(
self, self.problem.pyomo_model_objective, self._best_objective)
tmp_optbound_name = add_tmp_component(self.problem.pyomo_model,
"optimality_bound",
tmp_optbound)
self.range_reduction_constraint_added(tmp_optbound)
try:
return self._tighten_bounds_impl(tmp_objective)
finally:
# reset objective
delattr(self.problem.pyomo_model, tmp_objective_name)
self.problem.pyomo_model_objective.activate()
self.range_reduction_objective_changed(
self.problem.pyomo_model_objective)
# remove optimality bound if it was added
if tmp_optbound is not None:
self.range_reduction_constraint_removed(tmp_optbound)
delattr(self.problem.pyomo_model, tmp_optbound_name)
self.range_reduction_model_cleanup()
def test_create_optimality_bound(self):
# max
problem = MaxProblem()
model = pmo.block()
model.objective = pmo.objective(sense=pmo.maximize)
con = create_optimality_bound(problem, model.objective, 100)
assert con.ctype is pmo.constraint._ctype
assert con.body is model.objective
assert con.lb == 100
# min
problem = MinProblem()
model = pmo.block()
model.objective = pmo.objective(sense=pmo.minimize)
con = create_optimality_bound(problem, model.objective, 100)
assert con.ctype is pmo.constraint._ctype
assert con.body is model.objective
assert con.ub == 100