text: from artap.benchmark_robust import Synthetic2D
  from artap.algorithm_genetic import EpsMOEA
  from artap.algorithm import EvaluatorType
  from artap.results import Results
  import pylab as plt
  import artap.colormaps as cmaps
  
  
  if __name__ == '__main__':
      problem = Synthetic2D()
      algorithm = EpsMOEA(problem, evaluator_type=EvaluatorType.WORST_CASE)
      algorithm.options['max_population_size'] = 200
      algorithm.options['max_population_number'] = 100
      algorithm.run()
      fig = plt.figure()
      ax = fig.gca(projection='3d')
      [x, y, z] = problem.get_data_2d()
      ax.plot_surface(x, y, z, cmap=cmaps.viridis,
                      linewidth=0, antialiased=True)
  
      for individual in problem.last_population():
          x_1 = individual.vector[0]
          x_2 = individual.vector[1]
          y = individual.costs[0]
          ax.scatter(x_1, x_2, y, color='red', marker='o')
  
          for child in individual.children:
              x_1 = child.vector[0]
              x_2 = child.vector[1]
              y = child.costs[0]
              ax.scatter(x_1, x_2, y, color='black', marker='o')
      plt.show()
  
      results = Results(problem)
  