def test_infeasible_lp(self):
with SolverFactory("cplex", solver_io="python") as opt:
model = ConcreteModel()
model.X = Var(within=NonNegativeReals)
model.C1 = Constraint(expr=model.X == 1)
model.C2 = Constraint(expr=model.X == 2)
model.O = Objective(expr=model.X)
results = opt.solve(model)
self.assertEqual(results.solver.termination_condition,
TerminationCondition.infeasible)
def setUp(self):
opt = SolverFactory("cplex", solver_io="python")
model = ConcreteModel()
model.X = Var(within=NonNegativeReals, initialize=0)
model.Y = Var(within=NonNegativeReals, initialize=0)
model.C1 = Constraint(expr=2 * model.X + model.Y >= 8)
model.C2 = Constraint(expr=model.X + 3 * model.Y >= 6)
model.O = Objective(expr=model.X + model.Y)
opt.solve(model, load_solutions=False, save_results=False)
self._model = model
self._opt = opt
def test_soln_limit_mip(self):
with SolverFactory("cplex", solver_io="python") as opt:
model = ConcreteModel()
model.X = Var(within=Binary)
model.C1 = Constraint(expr=model.X == 1)
model.O = Objective(expr=model.X)
opt.options['mip_limits_solutions'] = 1
results = opt.solve(model)
self.assertEqual(results.solver.status, SolverStatus.aborted)
self.assertEqual(results.solver.termination_condition,
TerminationCondition.maxEvaluations)
self.assertEqual(model.solutions[0].status,
SolutionStatus.stoppedByLimit)
def test_get_duals_lp(self):
with SolverFactory("cplex", solver_io="python") as opt:
model = ConcreteModel()
model.X = Var(within=NonNegativeReals)
model.Y = Var(within=NonNegativeReals)
model.C1 = Constraint(expr=2 * model.X + model.Y >= 8)
model.C2 = Constraint(expr=model.X + 3 * model.Y >= 6)
model.O = Objective(expr=model.X + model.Y)
results = opt.solve(model, suffixes=['dual'], load_solutions=False)
model.dual = Suffix(direction=Suffix.IMPORT)
model.solutions.load_from(results)
self.assertAlmostEqual(model.dual[model.C1], 0.4)
self.assertAlmostEqual(model.dual[model.C2], 0.2)