input: Write a python function to create a population of individuals using a genetic algorithm with a fitness calculation that includes an additional parameter.
  assert len(create_population(10, -5, 5)) == 10
  assert create_population(1, -5, 5).shape == (1, 5)
  assert all(-5 <= individuum[i] <= 5 for individuum in create_population(5, -5, 5) for i in range(4))
output: import numpy as np
  
  def create_population(size, lower_bound, upper_bound):
      """
      Creates a population of individuals for a genetic algorithm.
      
      Parameters:
      size (int): The number of individuals in the population.
      lower_bound (int): The lower bound of the gene values.
      upper_bound (int): The upper bound of the gene values.
      
      Returns:
      np.ndarray: A numpy array representing the population.
      """
      return np.random.uniform(lower_bound, upper_bound, (size, 5))