input: def solve_linear_programming_problem_using_simplex_method_in_python():
      """Explain the approach for solving a linear programming problem using the Simplex method in Python.
      Example:
      No test cases provided as this function does not take in any input or return any output. It is a conceptual explanation.
      """
output:     # Step 1: Convert the problem into standard form
      # Ensure all constraints are in the form of equations (i.e., <= constraints)
      # Introduce slack variables to convert inequality constraints into equality constraints
  
      # Step 2: Set up the initial Simplex tableau
      # The initial tableau includes the objective function and the constraints
      # The objective function is usually represented in the bottom row of the tableau
  
      # Step 3: Determine the entering variable
      # Choose the most negative coefficient in the objective function row (bottom row)
      # This variable will enter the basis
  
      # Step 4: Determine the leaving variable
      # For each constraint, calculate the ratio of the right-hand side (RHS) to the coefficient of the entering variable
      # The leaving variable is the one with the smallest non-negative ratio
  
      # Step 5: Perform the pivot operation
      # Make the entering variable the basic variable in the row of the leaving variable
      # Update the tableau by performing row operations to make the column of the entering variable a unit vector
  
      # Step 6: Check for optimality
      # If there are no negative coefficients in the objective function row, the solution is optimal
      # If there are negative coefficients, repeat steps 3-5
  
      # Step 7: Extract the solution
      # The optimal values of the decision variables are found in the RHS of the final tableau
      # The optimal value of the objective function is the value in the bottom-right corner of the tableau