def solve_parametric():
m = create_warehouse_model(num_locations=50, num_customers=50)
opt = pyo.SolverFactory('gurobi')
p_values = list(range(1, 31))
obj_values = list()
for p in p_values:
m.P.value = p
res = opt.solve(m)
assert_optimal_termination(res)
obj_values.append(res.problem.lower_bound)
def solve_parametric_persistent():
m = create_warehouse_model(num_locations=50, num_customers=50)
opt = pyo.SolverFactory('gurobi_persistent')
opt.set_instance(m)
p_values = list(range(1, 31))
obj_values = list()
for p in p_values:
m.P.value = p
opt.remove_constraint(m.num_warehouses)
opt.add_constraint(m.num_warehouses)
res = opt.solve(save_results=False)
assert_optimal_termination(res)
obj_values.append(res.problem.lower_bound)
def _ip_helper(self, with_bounds, with_ineq, linear_solver):
t0 = 0
delta_t = 1
num_finite_elements = 90
constant_control_duration = 10
time_scale = 0.1
num_time_blocks = 3
interface = Problem(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
num_time_blocks=num_time_blocks,
with_bounds=with_bounds,
with_ineq=with_ineq)
options = parapint.algorithms.IPOptions()
options.linalg.solver = linear_solver
status = parapint.algorithms.ip_solve(interface=interface, options=options)
self.assertEqual(status, parapint.algorithms.InteriorPointStatus.optimal)
interface.load_primals_into_pyomo_model()
x = dict()
p = dict()
local_block_indices = _distribute_blocks(num_time_blocks, rank, size)
for ndx in local_block_indices:
m = interface.pyomo_model(ndx)
for t in m.x_time_points:
if t in x:
self.assertAlmostEqual(x[t], m.x[t].value)
else:
x[t] = m.x[t].value
for t in m.p_time_points:
p[t] = m.p[t].value
m = build_time_block(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
with_bounds=with_bounds,
with_ineq=with_ineq)
opt = pe.SolverFactory('ipopt')
res = opt.solve(m, tee=True)
assert_optimal_termination(res)
for _t, _x in x.items():
self.assertAlmostEqual(_x, m.x[_t].value)
for _t, _p in p.items():
self.assertAlmostEqual(_p, m.p[_t].value)
def test_kkt_system(self):
t0 = 0
delta_t = 1
num_finite_elements = 90
constant_control_duration = 10
time_scale = 0.1
num_time_blocks = 3
interface = Problem(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
num_time_blocks=num_time_blocks)
interface.set_primals(interface.init_primals())
interface.set_slacks(interface.init_slacks())
interface.set_duals_eq(interface.init_duals_eq())
interface.set_duals_ineq(interface.init_duals_ineq())
interface.set_duals_primals_lb(interface.init_duals_primals_lb())
interface.set_duals_primals_ub(interface.init_duals_primals_ub())
interface.set_duals_slacks_lb(interface.init_duals_slacks_lb())
interface.set_duals_slacks_ub(interface.init_duals_slacks_ub())
interface.set_barrier_parameter(0)
kkt = interface.evaluate_primal_dual_kkt_matrix()
rhs = interface.evaluate_primal_dual_kkt_rhs()
linear_solver = parapint.linalg.ScipyInterface()
linear_solver.do_symbolic_factorization(kkt)
linear_solver.do_numeric_factorization(kkt)
sol = linear_solver.do_back_solve(rhs)
interface.set_primal_dual_kkt_solution(sol)
interface.set_primals(interface.get_primals() + interface.get_delta_primals())
interface.set_slacks(interface.get_slacks() + interface.get_delta_slacks())
interface.set_duals_eq(interface.get_duals_eq() + interface.get_delta_duals_eq())
interface.set_duals_ineq(interface.get_duals_ineq() + interface.get_delta_duals_ineq())
interface.set_duals_primals_lb(interface.get_duals_primals_lb() + interface.get_delta_duals_primals_lb())
interface.set_duals_primals_ub(interface.get_duals_primals_ub() + interface.get_delta_duals_primals_ub())
interface.set_duals_slacks_lb(interface.get_duals_slacks_lb() + interface.get_delta_duals_slacks_lb())
interface.set_duals_slacks_ub(interface.get_duals_slacks_ub() + interface.get_delta_duals_slacks_ub())
interface.load_primals_into_pyomo_model()
x = dict()
p = dict()
for ndx in range(num_time_blocks):
m = interface.pyomo_model(ndx)
for t in m.x_time_points:
if t in x:
self.assertAlmostEqual(x[t], m.x[t].value)
else:
x[t] = m.x[t].value
for t in m.p_time_points:
p[t] = m.p[t].value
m = build_time_block(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale)
opt = pe.SolverFactory('ipopt')
res = opt.solve(m)
assert_optimal_termination(res)
for _t, _x in x.items():
self.assertAlmostEqual(_x, m.x[_t].value)
for _t, _p in p.items():
self.assertAlmostEqual(_p, m.p[_t].value)
def solve_warehouse_location(m):
opt = pyo.SolverFactory('gurobi')
res = opt.solve(m)
assert_optimal_termination(res)