Beispiel #1
0
    def configure(self):
        """ Creates a new Assembly with this problem

        Optimal Design at (1.9776, 0, 0)

        Optimal Objective = 3.18339
        """

        self.add('driver', FixedPointIterator())

        # Inner Loop - Full Multidisciplinary Solve via fixed point iteration
        C1 = self.add('C1', sellar.Discipline1_WithDerivatives())
        C2 = self.add('C2', sellar.Discipline2_WithDerivatives())

        self.driver.workflow.add(['C1','C2'])

        #not relevant to the iteration. Just fixed constants
        C1.z1 = C2.z1 = 1.9776
        C1.z2 = C2.z2 = 0
        C1.x1 = 0

        # Solver settings
        self.driver.max_iteration = 5
        self.driver.tolerance = 1.e-15
        self.driver.print_convergence = False
    def configure(self):
        """ Creates a new Assembly with this problem
        
        Optimal Design at (1.9776, 0, 0)
        
        Optimal Objective = 3.18339"""

        # create Optimizer instance
        self.add('driver', SLSQPdriver())

        # Outer Loop - Global Optimization
        self.add('dummy', Dummy())
        self.dummy.force_execute = True
        self.add('solver', FixedPointIterator())
        self.driver.workflow.add(['dummy', 'solver'])

        # Inner Loop - Full Multidisciplinary Solve via fixed point iteration
        self.add('dis1', sellar.Discipline1_WithDerivatives())
        self.add('dis2', sellar.Discipline2_WithDerivatives())
        self.solver.workflow.add(['dis1', 'dis2'])

        # Add Parameters to optimizer
        self.driver.add_parameter(('dis1.z1', 'dis2.z1'), low=-10.0, high=10.0)
        self.driver.add_parameter(('dis1.z2', 'dis2.z2'), low=0.0, high=10.0)
        self.driver.add_parameter('dis1.x1', low=0.0, high=10.0)

        # Make all connections
        self.connect('dis1.y1', 'dis2.y1')

        # Iteration loop
        self.solver.add_parameter('dis1.y2', low=-1.e99, high=1.e99)
        self.solver.add_constraint('dis2.y2 = dis1.y2')

        # Solver settings
        self.solver.max_iteration = 100
        self.solver.tolerance = .00001
        self.solver.print_convergence = False

        # Optimization parameters
        self.driver.add_objective(
            '(dis1.x1)**2 + dis1.z2 + dis1.y1 + math.exp(-dis2.y2)')

        self.driver.add_constraint('3.16 < dis1.y1')
        self.driver.add_constraint('dis2.y2 < 24.0')

        self.driver.iprint = 0
    def configure(self):
        """ Creates a new Assembly with this problem

        Optimal Design at (1.9776, 0, 0)

        Optimal Objective = 3.18339"""

        # create Optimizer instance
        self.add('driver', SLSQPdriver())

        # Disciplines
        self.add('dis1', sellar.Discipline1_WithDerivatives())
        self.add('dis2', sellar.Discipline2_WithDerivatives())

        # Driver process definition
        self.driver.workflow.add(['dis1', 'dis2'])
        #self.driver.workflow.add(['dis1'])

        # Optimization parameters
        self.driver.add_objective(
            '(dis1.x1)**2 + dis1.z2 + dis1.y1 + math.exp(-dis2.y2)')

        #Global Design Variables
        self.driver.add_parameter(('dis1.z1', 'dis2.z1'), low=-10.0, high=10.0)
        self.driver.add_parameter(('dis1.z2', 'dis2.z2'), low=0.0, high=10.0)

        #Local Design Variables and Coupling Variables
        self.driver.add_parameter('dis1.x1', low=0.0, high=10.0)
        self.driver.add_parameter('dis2.y1', low=-1e99, high=1e99)
        self.driver.add_parameter('dis1.y2', low=-1e99, high=1e99)
        self.driver.add_constraint('3.16 < dis1.y1')
        self.driver.add_constraint('dis2.y2 < 24.0')

        self.driver.add_constraint('(dis2.y1-dis1.y1)**2 <= 0')
        self.driver.add_constraint('(dis2.y2-dis1.y2)**2 <= 0')

        self.driver.iprint = 0