def configure(self):
self.add('driver', IterateUntil())
self.add('branchbound_algorithm', BranchBoundNonLinear(n_int = 2, n_contin = 0))
#self.add('nonlinopt', BandBSLSQPdriver(n_x=2))
self.add('nonlinopt', pyOptSparseDriver(n_x=2))
self.nonlinopt.optimizer = "SNOPT"
self.add('nonlin_test_prob', NonLinearTestProblem())
#nonlin problem formulation`
self.nonlinopt.add_parameter('nonlin_test_prob.x', low=0, high=1e3)
self.nonlinopt.add_objective('nonlin_test_prob.f')
self.nonlinopt.add_constraint('nonlin_test_prob.g1 < 0')
self.nonlinopt.add_constraint('nonlin_test_prob.g2 < 0')
#iteration hierachy
self.driver.workflow.add(['branchbound_algorithm','nonlinopt'])
self.nonlinopt.workflow.add('nonlin_test_prob')
#data connections
# Connect solver component with the Branch and Bound Algorithm Component (return results)
self.connect('nonlin_test_prob.x', 'branchbound_algorithm.xopt_current')
self.connect('nonlin_test_prob.f', 'branchbound_algorithm.relaxed_obj_current')
self.connect('nonlinopt.exit_flag', 'branchbound_algorithm.exitflag_NLP')
# Connect Airline Allocation SubProblem Component with Branch and Bound Algorithm Component and the solver
# Connect Branch and Bound Algorithm Component with the solver component
self.connect('branchbound_algorithm.lb', 'nonlinopt.lb')
self.connect('branchbound_algorithm.ub', 'nonlinopt.ub')
self.driver.add_stop_condition('branchbound_algorithm.exec_loop != 0')
self.driver.max_iterations = 1000000
self.recorders=[JSONCaseRecorder('nonlintest.json')]
def configure(self):
""" Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
# Create MultiFunction component instances
self.add('multifunction', MultiFunction())
# Create NSGA2 Optimizer instance
self.add('driver', pyOptSparseDriver())
# Driver process definition
self.driver.workflow.add('multifunction')
self.driver.print_results = False
# NSGA2 Objective
self.driver.add_objective('multifunction.f1_x')
self.driver.add_objective('multifunction.f2_x')
# NSGA2 Design Variable
self.driver.add_parameter('multifunction.x1', low=0.1, high=1.0)
self.driver.add_parameter('multifunction.x2', low=0.0, high=5.0)
# NSGA2 Constraints
self.driver.add_constraint('multifunction.g1_x >= 6.0')
self.driver.add_constraint('multifunction.g2_x >= 1.0')
def configure(self):
""" Creates a new Assembly containing a Paraboloid and an optimizer"""
# pylint: disable=E1101
# Create Paraboloid component instances
self.add('paraboloid', Paraboloid())
# Create SNOPT Optimizer instance
self.add('driver', pyOptSparseDriver(n_x=2))
# Driver process definition
self.driver.workflow.add('paraboloid')
# SNOPT Objective
self.driver.add_objective('paraboloid.f_xy')
# SNOPT Design Variables
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_parameter('paraboloid.y', low=-50., high=50.)
self.driver.lb = [0.,0.]
self.driver.ub = [5,100.0]
# SNOPT Constraints
self.driver.add_constraint('paraboloid.x-paraboloid.y >= 15.0')
self.driver.print_results = False
def configure(self):
""" Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
# Create MultiFunction component instances
self.add('multifunction', MultiFunction())
# Create NSGA2 Optimizer instance
self.add('driver', pyOptSparseDriver())
# Driver process definition
self.driver.workflow.add('multifunction')
self.driver.print_results = False
# NSGA2 Objective
self.driver.add_objective('multifunction.f1_x')
self.driver.add_objective('multifunction.f2_x')
# NSGA2 Design Variable
self.driver.add_parameter('multifunction.x1', low=0.1, high=1.0)
self.driver.add_parameter('multifunction.x2', low=0.0, high=5.0)
# NSGA2 Constraints
self.driver.add_constraint('multifunction.g1_x >= 6.0')
self.driver.add_constraint('multifunction.g2_x >= 1.0')
def configure(self):
""" Creates a new Assembly containing a Paraboloid and an optimizer"""
# pylint: disable=E1101
# Create Paraboloid component instances
self.add('paraboloid', Paraboloid())
# Create SNOPT Optimizer instance
self.add('driver', pyOptSparseDriver(n_x=2))
# Driver process definition
self.driver.workflow.add('paraboloid')
# SNOPT Objective
self.driver.add_objective('paraboloid.f_xy')
# SNOPT Design Variables
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_parameter('paraboloid.y', low=-50., high=50.)
self.driver.lb = [0., 0.]
self.driver.ub = [5, 100.0]
# SNOPT Constraints
self.driver.add_constraint('paraboloid.x-paraboloid.y >= 15.0')
self.driver.print_results = False
def configure(self):
""" Creates a new Assembly containing ArrayParaboloid and an optimizer"""
# pylint: disable=E1101
self.add('paraboloid', ArrayParaboloid())
self.add('driver', pyOptSparseDriver())
self.driver.pyopt_diff = True
self.driver.workflow.add('paraboloid')
self.driver.add_objective('paraboloid.f_xy')
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_constraint('paraboloid.x[0]-paraboloid.x[1] >= 15.0')
self.driver.print_results = False
def configure(self):
""" Creates a new Assembly containing ArrayParaboloid and an optimizer"""
# pylint: disable=E1101
self.add('paraboloid', ArrayParaboloid())
self.add('driver', pyOptSparseDriver())
self.driver.pyopt_diff = True
self.driver.workflow.add('paraboloid')
self.driver.add_objective('paraboloid.f_xy')
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_constraint('paraboloid.x[0]-paraboloid.x[1] >= 15.0')
self.driver.print_results = False
def configure(self):
self.add('driver', pyOptSparseDriver(n_x=2))
self.driver.optimizer = "SNOPT"
self.add('prob', NonLinearTestProblem())
self.driver.add_parameter('prob.x', low=0, high=1000)
self.driver.gradient_options.fd_form = 'central'
self.driver.gradient_options.fd_step = 1.0e-3
self.driver.gradient_options.fd_step_type = 'relative'
self.driver.add_objective('prob.f')
self.driver.add_constraint('prob.g1 < 0')
self.driver.add_constraint('prob.g2 < 0')
def configure(self):
self.add('driver', pyOptSparseDriver(n_x=2))
self.driver.optimizer = "SNOPT"
self.add('prob', NonLinearTestProblem())
self.driver.add_parameter('prob.x', low=0, high=1000)
self.driver.gradient_options.fd_form = 'central'
self.driver.gradient_options.fd_step = 1.0e-3
self.driver.gradient_options.fd_step_type = 'relative'
self.driver.add_objective('prob.f')
self.driver.add_constraint('prob.g1 < 0')
self.driver.add_constraint('prob.g2 < 0')
def __init__(self):
"""Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
super(BenchMarkOptimization, self).__init__()
# Create MultiFunction component instances
self.add('benchmark', BenchMark())
# Create ALPSO Optimizer instance
self.add('driver', pyOptSparseDriver())
# Driver process definition
self.driver.workflow.add('benchmark')
# PyOpt Flags
self.driver.optimizer = 'ALPSO'
self.driver.title = 'Bench mark problem 4 - Unconstrained'
optdict = {}
optdict['SwarmSize'] = 40
optdict['maxOuterIter'] = 100
optdict['maxInnerIter'] = 3
optdict['minInnerIter'] = 3
optdict['etol'] = 1e-4
optdict['itol'] = 1e-4
optdict['c1'] = 0.8
optdict['c2'] = 0.8
optdict['w1'] = 0.9
optdict['nf'] = 5
optdict['dt'] = 1.0
optdict['vcrazy'] = 1e-4
optdict['Scaling'] = 1
optdict['seed'] = 1.0
self.driver.options = optdict
# ALPSO Objective
self.driver.add_objective('benchmark.f_x')
# ALPSO Design Variables
self.driver.add_parameter('benchmark.x1', low=0, high=42)
self.driver.add_parameter('benchmark.x2', low=0, high=42)
self.driver.add_parameter('benchmark.x3', low=0, high=42)
# ALPSO Constraints
self.driver.add_constraint('benchmark.g1_x <= 0.0')
self.driver.add_constraint('benchmark.h1_x <= 0.0')
def __init__(self):
"""Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
super(BenchMarkOptimization, self).__init__()
# Create MultiFunction component instances
self.add('benchmark', BenchMark())
# Create ALPSO Optimizer instance
self.add('driver', pyOptSparseDriver())
# Driver process definition
self.driver.workflow.add('benchmark')
# PyOpt Flags
self.driver.optimizer = 'ALPSO'
self.driver.title = 'Bench mark problem 4 - Unconstrained'
optdict = {}
optdict['SwarmSize'] = 40
optdict['maxOuterIter'] = 100
optdict['maxInnerIter'] = 3
optdict['minInnerIter'] = 3
optdict['etol'] = 1e-4
optdict['itol'] = 1e-4
optdict['c1'] = 0.8
optdict['c2'] = 0.8
optdict['w1'] = 0.9
optdict['nf'] = 5
optdict['dt'] = 1.0
optdict['vcrazy'] = 1e-4
optdict['Scaling'] = 1
optdict['seed'] = 1.0
self.driver.options = optdict
# ALPSO Objective
self.driver.add_objective('benchmark.f_x')
# ALPSO Design Variables
self.driver.add_parameter('benchmark.x1', low=0, high=42)
self.driver.add_parameter('benchmark.x2', low=0, high=42)
self.driver.add_parameter('benchmark.x3', low=0, high=42)
# ALPSO Constraints
self.driver.add_constraint('benchmark.g1_x <= 0.0')
self.driver.add_constraint('benchmark.h1_x <= 0.0')
def configure(self):
self.add('driver', IterateUntil())
self.add('branchbound_algorithm',
BranchBoundNonLinear(n_int=2, n_contin=0))
#self.add('nonlinopt', BandBSLSQPdriver(n_x=2))
self.add('nonlinopt', pyOptSparseDriver(n_x=2))
self.nonlinopt.optimizer = "SNOPT"
self.add('nonlin_test_prob', NonLinearTestProblem())
#nonlin problem formulation`
self.nonlinopt.add_parameter('nonlin_test_prob.x', low=0, high=1e3)
self.nonlinopt.add_objective('nonlin_test_prob.f')
self.nonlinopt.add_constraint('nonlin_test_prob.g1 < 0')
self.nonlinopt.add_constraint('nonlin_test_prob.g2 < 0')
#iteration hierachy
self.driver.workflow.add(['branchbound_algorithm', 'nonlinopt'])
self.nonlinopt.workflow.add('nonlin_test_prob')
#data connections
# Connect solver component with the Branch and Bound Algorithm Component (return results)
self.connect('nonlin_test_prob.x',
'branchbound_algorithm.xopt_current')
self.connect('nonlin_test_prob.f',
'branchbound_algorithm.relaxed_obj_current')
self.connect('nonlinopt.exit_flag',
'branchbound_algorithm.exitflag_NLP')
# Connect Airline Allocation SubProblem Component with Branch and Bound Algorithm Component and the solver
# Connect Branch and Bound Algorithm Component with the solver component
self.connect('branchbound_algorithm.lb', 'nonlinopt.lb')
self.connect('branchbound_algorithm.ub', 'nonlinopt.ub')
self.driver.add_stop_condition('branchbound_algorithm.exec_loop != 0')
self.driver.max_iterations = 1000000
self.recorders = [JSONCaseRecorder('nonlintest.json')]
num_cp = num_cp_init
while num_cp <= num_cp_max:
x_range *= 1.852
x_init = x_range * 1e3 * (
1 - np.cos(np.linspace(0, 1, num_cp) * np.pi)) / 2 / 1e6
M_init = np.ones(num_cp) * 0.82
h_init = 10 * np.sin(np.pi * x_init / (x_range / 1e3))
model = set_as_top(
MissionSegment(num_elem=num_elem,
num_cp=num_cp,
x_pts=x_init,
surr_file='crm_surr'))
model.replace('driver', pyOptSparseDriver())
#model.replace('driver', SimpleDriver())
model.driver.optimizer = 'SNOPT'
model.driver.options = {'Iterations limit': 5000000}
# Add parameters, objectives, constraints
model.driver.add_parameter('h_pt', low=0.0, high=14.1)
model.driver.add_objective('SysFuelObj.fuelburn')
model.driver.add_constraint('SysHBspline.h[0] = 0.0')
model.driver.add_constraint('SysHBspline.h[-1] = 0.0')
model.driver.add_constraint('SysTmin.Tmin < 0.0')
model.driver.add_constraint('SysTmax.Tmax < 0.0')
model.driver.add_constraint('%.15f < SysGammaBspline.Gamma < %.15f' % \
(gamma_lb, gamma_ub), linear=True)
# Initial value of the parameter
start = time.time()
num_cp = num_cp_init
while num_cp <= num_cp_max:
x_range *= 1.852
x_init = x_range * 1e3 * (1-np.cos(np.linspace(0, 1, num_cp)*np.pi))/2/1e6
#v_init = np.ones(num_cp)*2.5
M_init = np.ones(num_cp)*0.8
#M_init = np.ones(num_cp)*0.82
h_init = 10 * np.sin(np.pi * x_init / (x_range/1e3))
model = set_as_top(MissionSegment(num_elem=num_elem, num_cp=num_cp,
x_pts=x_init, surr_file='../crm_surr'))
model.replace('driver', pyOptSparseDriver())
#model.replace('driver', SimpleDriver())
model.driver.optimizer = 'SNOPT'
model.driver.options = {'Iterations limit': 5000000,
'Print file': os.path.join('plotting','range_sweep_data','SNOPT_%d_print.out' % num_cp)}
# Add parameters, objectives, constraints
model.driver.add_parameter('h_pt', low=0.0, high=14.1)
model.driver.add_objective('SysFuelObj.fuelburn')
model.driver.add_constraint('SysHi.h_i = 0.0')
model.driver.add_constraint('SysHf.h_f = 0.0')
model.driver.add_constraint('SysTmin.Tmin < 0.0')
model.driver.add_constraint('SysTmax.Tmax < 0.0')
model.driver.add_constraint('%.15f < SysGammaBspline.Gamma < %.15f' % \
(gamma_lb, gamma_ub), linear=True)
print alloc.SysProfit.profit
#alloc.check_comp_derivatives()
exit()
# for irt in xrange(alloc.num_routes):
# for inac in xrange(alloc.num_new_ac):
# seg_name = 'Seg_%03i_%03i' % (irt,inac)
# seg = alloc.get(seg_name)
# sub_opt = setup_opt(seg)
#
# sub_opt.run()
#
# call(['mv', 'SNOPT_print.out', 'SNOPT_%03i_%03i_print.out' % (irt,inac)])
# call(['rm', 'SNOPT_summary.out'])
alloc.replace('driver', pyOptSparseDriver())
alloc.driver.optimizer = 'SNOPT'
alloc.driver.options = {'Iterations limit': 5000000}#, 'Verify level':3}
# alloc.driver.gradient_options.lin_solver = "linear_gs"
alloc.driver.gradient_options.lin_solver = 'petsc_ksp'
# alloc.driver.gradient_options.maxiter = 1
alloc.driver.gradient_options.derivative_direction = 'adjoint'
alloc.driver.gradient_options.iprint = 0
# alloc.driver.system_type = 'serial'
alloc.driver.add_objective('profit')
for irt in xrange(alloc.num_routes):
for inac in xrange(alloc.num_new_ac):
seg_name = 'Seg_%03i_%03i' % (irt,inac)
alloc.driver.add_parameter(seg_name+'.h_pt', low=0.0, high=15.0) #14.1)
alloc.driver.add_constraint(seg_name+'.h[0] = 0.0')
