Loops OpenMDAO v0.13：使用在循环中启动的组件的多个实例时执行优化

我正在OpenMDAO v0.13中使用多次使用的几个组件进行优化。我的程序集似乎与默认驱动程序配合得很好，但当我使用优化器运行时，它无法解决问题。优化器只是使用给定的输入运行，并使用这些输入返回答案。我不确定问题是什么，但我希望有任何见解。我已经包括了一个简单的代码模仿我的结构，复制错误。我认为问题在于连接，summer.fs在初始化后不会更新

from openmdao.main.api import Assembly, Component
from openmdao.lib.datatypes.api import Float, Array, List
from openmdao.lib.drivers.api import DOEdriver, SLSQPdriver, COBYLAdriver, CaseIteratorDriver
from pyopt_driver.pyopt_driver import pyOptDriver

import numpy as np


class component1(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='out')
    a = Float(iotype='in', default_value=1)
    def execute(self):
        x = self.x
        a = self.a

        term1 = a*x**2
        self.term1 = term1

        print "In comp1", self.name, self.a, self.x, self.term1

    def list_deriv_vars(self):
        return ('x',), ('term1',)

    def provideJ(self):

        x = self.x
        a = self.a
        dterm1_dx = 2.*a*x

        J = np.array([[dterm1_dx]])
        print 'In comp1, J = %s' % J

        return J


class component2(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='in')
    f = Float(iotype='out')

    def execute(self):

        y = self.y
        x = self.x
        term1 = self.term1
        f = term1 + x + y**2

        self.f = f
        print "In comp2", self.name, self.x, self.y, self.term1, self.f



class summer(Component):


    total = Float(iotype='out', desc='sum of all f values')

    def __init__(self, size):
        super(summer, self).__init__()
        self.size = size

        self.add('fs', Array(np.ones(size), iotype='in', desc='f values from all cases'))

    def execute(self):
        self.total = sum(self.fs)
        print 'In summer, fs = %s and total = %s' % (self.fs, self.total)


class assembly(Assembly):

    x = Float(iotype='in')
    y = Float(iotype='in')
    total = Float(iotype='out')

    def __init__(self, size):

        super(assembly, self).__init__()

        self.size = size

        self.add('a_vals', Array(np.zeros(size), iotype='in', dtype='float'))
        self.add('fs', Array(np.zeros(size), iotype='out', dtype='float'))

        print 'in init a_vals = %s' % self.a_vals


    def configure(self):

        # self.add('driver', SLSQPdriver())
        self.add('driver', pyOptDriver())
        self.driver.optimizer = 'SNOPT'
        # self.driver.pyopt_diff = True

        #create this first, so we can connect to it
        self.add('summer', summer(size=len(self.a_vals)))
        self.connect('summer.total', 'total')

        print 'in configure a_vals = %s' % self.a_vals

        # create instances of components
        for i in range(0, self.size):
            c1 = self.add('comp1_%d'%i, component1())
            c1.missing_deriv_policy = 'assume_zero'

            c2 = self.add('comp2_%d'%i, component2())
            self.connect('a_vals[%d]' % i, 'comp1_%d.a' % i)
            self.connect('x', ['comp1_%d.x'%i, 'comp2_%d.x'%i])
            self.connect('y', ['comp1_%d.y'%i, 'comp2_%d.y'%i])
            self.connect('comp1_%d.term1'%i, 'comp2_%d.term1'%i)

            self.connect('comp2_%d.f'%i, 'summer.fs[%d]'%i)

            self.driver.workflow.add(['comp1_%d'%i, 'comp2_%d'%i])

        self.connect('summer.fs[:]', 'fs[:]')
        self.driver.workflow.add(['summer'])

        # set up main driver (optimizer)
        self.driver.iprint = 1
        self.driver.maxiter = 100
        self.driver.accuracy = 1.0e-6
        self.driver.add_parameter('x', low=-5., high=5.)
        self.driver.add_parameter('y', low=-5., high=5.)
        self.driver.add_objective('summer.total')


if __name__ == "__main__":
    """ the result should be -1 at (x, y) = (-0.5, 0) """

    import time
    from openmdao.main.api import set_as_top
    a_vals = np.array([1., 1., 1., 1.])
    test = set_as_top(assembly(size=len(a_vals)))
    test.a_vals = a_vals
    print test.a_vals
    test.x = 2.
    test.y = 2.

    tt = time.time()
    test.run()

    print "Elapsed time: ", time.time()-tt, "seconds"

    print 'result = ', test.summer.total
    print '(x, y) = (%s, %s)' % (test.x, test.y)
    print test.fs

---

我对您的模型进行了研究，发现以下行导致了问题：

#self.connect('summer.fs[:]', 'fs[:]')

当我把它注释掉时，我得到了移动的优化

---

我不确定那里发生了什么，但图形转换有时会在组件输入节点（在部件边界上提升为输出）方面出现一些问题。如果仍希望这些值在程序集上可用，则可以尝试升级来自

comp2\n

组件的输出。

谢谢，删除将输入节点升级为程序集边界上输出的行解决了问题。