code: def global_optimum(self):
          
          x = [random.uniform(0, 1) for _ in range(self.objectives - 1)]
          x.extend([0.5 for _ in range(self.dimensions - self.objectives + 1)])
          return x
docs: Return a globally optimal solution to this problem.
          
          This function returns a globally optimal solution (i.e., a 
          solution that lives on the Pareto front). Since there are many
          solutions that are Pareto-optimal, this function randomly 
          chooses one to return.