input: Write a function to optimize a variable using gradient descent.
  assert optimize_variable(2, 0.1, 1000) == 0.0
  assert optimize_variable(10, 0.01, 1000) == 0.0
  assert optimize_variable(5, 0.05, 1000) == 0.0
output: def optimize_variable(initial_value, learning_rate, iterations):
      x = initial_value
      for _ in range(iterations):
          gradient = 2 * x
          x -= learning_rate * gradient
      return round(x, 1)