def test_GA_multi_obj_multi_con(self):
        # Note, just verifying that things work functionally, rather than run
        # this for many generations.

        try:
            from pyopt_driver.pyopt_driver import pyOptDriver
        except ImportError:
            raise SkipTest("this test requires pyOpt to be installed")

        self.top = MultiObjectiveOptimization()
        set_as_top(self.top)

        try:
            self.top.driver.optimizer = 'NSGA2'
        except __HOLE__:
            raise SkipTest("NSGA2 not present on this system")

        # PyOpt Flags
        self.top.driver.title = 'Two-Objective Fitness MultiFunction Test'
        optdict = {}
        optdict['PopSize'] = 100     #   a multiple of 4
        optdict['maxGen'] = 5
        optdict['pCross_real'] = 0.6 #prob of crossover of design variables in range (0.6-1.0)
        optdict['pMut_real'] = 0.5   #prob of mutation of (1/design varaibles)
        optdict['eta_c'] = 10.0      #distribution index for crossover in range (5 - 20)
        optdict['eta_m'] = 50.0      #distribution index for mutation in range (5 - 50)
        optdict['pCross_bin'] = 1.0  #prob of crossover of binary variable in range(0.6 - 1.0)
        optdict['pMut_real'] = 1.0   #prob of mutation of binary variables in (1/nbits)
        optdict['PrintOut'] = 0      #flag to turn on output to files (0-None, 1-Subset,2-All)
        optdict['seed'] = 0.0        #random seed number (0-autoseed based on time clock)

        self.top.driver.options = optdict

        self.top.run()
dataset/ETHPy150Open OpenMDAO-Plugins/pyopt_driver/src/pyopt_driver/test/test_pyopt_driver.py/pyOptDriverTestCase.test_GA_multi_obj_multi_con