input: from typing import List
  
  def optimize_objective_function(parameters: List[float]) -> List[float]:
      """Optimize the given objective function using the SciPy minimize function.
      
      >>> optimize_objective_function([0.0, 0.0, 0.0])
      [0.0, 0.0, 0.0]
      """
      
      from scipy.optimize import minimize
  
      def obj_func(x):
          # objective function
          # ...
          return x[0]**2 + x[1]**2 + x[2]**2
  
      x0 = parameters
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x
output:     from scipy.optimize import minimize
  
      def obj_func(x):
          # objective function
          # ...
          return x[0]**2 + x[1]**2 + x[2]**2
  
      x0 = parameters
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x