input: Write a function to optimize the given objective function using the scipy.optimize.minimize method. The function should return the optimized values of the variables.
  def obj_func(x):
      # objective function
      # ...
  
  def optimize(): 
      # set up optimization problem
      x0 = [0.0, 0.0, 0.0] 
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True}) 
      return res.x
  
  assert list(optimize())==[0.0, 0.0, 0.0]
output: def optimize(): 
      x0 = [0.0, 0.0, 0.0] 
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True}) 
      return res.x