input: def optimize_objective_function():
      """Given an objective function, write a python program to optimize it using `scipy.optimize.minimize`.
      >>> from scipy.optimize import minimize
      >>> def obj_func(x):
      ...     # some objective function
      ...     return (x[0] - 1)**2 + (x[1] - 2.5)**2 + (x[2] - 3)**2
      >>> 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
      >>> optimize()
      [1.0, 2.5, 3.0]
      """
output:     from scipy.optimize import minimize
      
      def obj_func(x):
          return (x[0] - 1)**2 + (x[1] - 2.5)**2 + (x[2] - 3)**2
      
      x0 = [0.0, 0.0, 0.0]
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x