def test_relaxation_feasibility(self):
m = models.makeNestedDisjunctions_FlatDisjuncts()
TransformationFactory('gdp.chull').apply_to(m)
solver = SolverFactory(linear_solvers[0])
cases = [
(1, 1, 1, 1, None),
(0, 0, 0, 0, None),
(1, 0, 0, 0, None),
(0, 1, 0, 0, 1.1),
(0, 0, 1, 0, None),
(0, 0, 0, 1, None),
(1, 1, 0, 0, None),
(1, 0, 1, 0, 1.2),
(1, 0, 0, 1, 1.3),
(1, 0, 1, 1, None),
]
for case in cases:
m.d1.indicator_var.fix(case[0])
m.d2.indicator_var.fix(case[1])
m.d3.indicator_var.fix(case[2])
m.d4.indicator_var.fix(case[3])
results = solver.solve(m)
print(case, results.solver)
if case[4] is None:
self.assertEqual(results.solver.termination_condition,
pyomo.opt.TerminationCondition.infeasible)
else:
self.assertEqual(results.solver.termination_condition,
pyomo.opt.TerminationCondition.optimal)
self.assertEqual(value(m.obj), case[4])
def test_relaxation_feasibility(self):
m = models.makeNestedDisjunctions_FlatDisjuncts()
TransformationFactory('gdp.chull').apply_to(m)
solver = SolverFactory(linear_solvers[0])
cases = [
(1,1,1,1,None),
(0,0,0,0,None),
(1,0,0,0,None),
(0,1,0,0,1.1),
(0,0,1,0,None),
(0,0,0,1,None),
(1,1,0,0,None),
(1,0,1,0,1.2),
(1,0,0,1,1.3),
(1,0,1,1,None),
]
for case in cases:
m.d1.indicator_var.fix(case[0])
m.d2.indicator_var.fix(case[1])
m.d3.indicator_var.fix(case[2])
m.d4.indicator_var.fix(case[3])
results = solver.solve(m)
print(case, results.solver)
if case[4] is None:
self.assertEqual(results.solver.termination_condition,
pyomo.opt.TerminationCondition.infeasible)
else:
self.assertEqual(results.solver.termination_condition,
pyomo.opt.TerminationCondition.optimal)
self.assertEqual(value(m.obj), case[4])
def test_deactivated_disjunct_leaves_nested_disjuncts_active(self):
m = models.makeNestedDisjunctions_FlatDisjuncts()
m.d1.deactivate()
# Specifying 'targets' prevents the HACK_GDP_Disjunct_Reclassifier
# transformation of Disjuncts to Blocks
TransformationFactory('gdp.chull').apply_to(m, targets=[m])
self.assertFalse(m.d1.active)
self.assertTrue(m.d1.indicator_var.fixed)
self.assertEqual(m.d1.indicator_var.value, 0)
self.assertFalse(m.d2.active)
self.assertFalse(m.d2.indicator_var.fixed)
self.assertTrue(m.d3.active)
self.assertFalse(m.d3.indicator_var.fixed)
self.assertTrue(m.d4.active)
self.assertFalse(m.d4.indicator_var.fixed)
m = models.makeNestedDisjunctions_NestedDisjuncts()
m.d1.deactivate()
# Specifying 'targets' prevents the HACK_GDP_Disjunct_Reclassifier
# transformation of Disjuncts to Blocks
TransformationFactory('gdp.chull').apply_to(m, targets=[m])
self.assertFalse(m.d1.active)
self.assertTrue(m.d1.indicator_var.fixed)
self.assertEqual(m.d1.indicator_var.value, 0)
self.assertFalse(m.d2.active)
self.assertFalse(m.d2.indicator_var.fixed)
self.assertTrue(m.d1.d3.active)
self.assertFalse(m.d1.d3.indicator_var.fixed)
self.assertTrue(m.d1.d4.active)
self.assertFalse(m.d1.d4.indicator_var.fixed)
def test_deactivated_disjunct_leaves_nested_disjuncts_active(self):
m = models.makeNestedDisjunctions_FlatDisjuncts()
m.d1.deactivate()
# Specifying 'targets' prevents the HACK_GDP_Disjunct_Reclassifier
# transformation of Disjuncts to Blocks
TransformationFactory('gdp.chull').apply_to(m, targets=[m])
self.assertFalse(m.d1.active)
self.assertTrue(m.d1.indicator_var.fixed)
self.assertEqual(m.d1.indicator_var.value, 0)
self.assertFalse(m.d2.active)
self.assertFalse(m.d2.indicator_var.fixed)
self.assertTrue(m.d3.active)
self.assertFalse(m.d3.indicator_var.fixed)
self.assertTrue(m.d4.active)
self.assertFalse(m.d4.indicator_var.fixed)
m = models.makeNestedDisjunctions_NestedDisjuncts()
m.d1.deactivate()
# Specifying 'targets' prevents the HACK_GDP_Disjunct_Reclassifier
# transformation of Disjuncts to Blocks
TransformationFactory('gdp.chull').apply_to(m, targets=[m])
self.assertFalse(m.d1.active)
self.assertTrue(m.d1.indicator_var.fixed)
self.assertEqual(m.d1.indicator_var.value, 0)
self.assertFalse(m.d2.active)
self.assertFalse(m.d2.indicator_var.fixed)
self.assertTrue(m.d1.d3.active)
self.assertFalse(m.d1.d3.indicator_var.fixed)
self.assertTrue(m.d1.d4.active)
self.assertFalse(m.d1.d4.indicator_var.fixed)
