input: 
  def solve_linear_programming_simplex(obj_coeffs, constraints, rhs):
      """Solves a linear programming problem using the Simplex method. The function takes
      the coefficients of the objective function, the coefficients and right-hand side of
      the constraints, and returns the optimal solution.
      
      >>> solve_linear_programming_simplex([3, 4], [[2, 1], [1, 3]], [10, 15])
      [3, 3]
      """
  
output:     from scipy.optimize import linprog
  
      # Convert the problem to the form expected by scipy.optimize.linprog
      c = [-coeff for coeff in obj_coeffs]  # Negate the objective coefficients for maximization
      A = constraints
      b = rhs
  
      # Solve the linear programming problem using the Simplex method
      result = linprog(c, A_ub=A, b_ub=b, method='simplex')
  
      # Check if the problem was successfully solved
      if result.success:
          return result.x.tolist()
      else:
          raise ValueError("The linear programming problem could not be solved.")