def opt(self, objective, parameter):
"""
The optimization procedure.
:param objective: an Objective object
:param parameter: a Parameter object
:return: the best solution
"""
self.clear()
if parameter.get_noise_handling() is True and parameter.get_ponss(
) is True:
self.__algorithm = PONSS()
else:
self.__algorithm = ParetoOpt()
self.__best_solution = self.__algorithm.opt(objective, parameter)
return self.__best_solution
def __init__(self):
ParetoOpt.__init__(self)
pass
def test_mutation(self):
a = [0, 1, 0, 1]
n = 4
res = ParetoOpt.mutation(a, n)
assert res != a