input: Write a function to explain the approach for solving a linear programming problem using the Simplex method in Python. The function should start by defining the problem in terms of decision variables, objective function, and constraints. Then it should convert the problem into standard form by introducing slack variables if needed, create a tableau, and set up the starting solution. Finally, it should use the Simplex algorithm iteratively to move from one vertex to the next until an optimum solution is found and determined by inspecting the values in the tableau.
  assert solve_lp_problem_simplex()=="First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."
  assert solve_lp_problem_simplex()=="First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."
  assert solve_lp_problem_simplex()=="First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."
  assert solve_lp_problem_simplex()=="First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."
  assert solve_lp_problem_simplex()=="First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."
output: def solve_lp_problem_simplex():
      return "First, define the problem in terms of decision variables, objective function, and constraints. Next, convert the problem into standard form by introducing slack variables, if needed. Create a tableau containing the coefficients of the decision variables and the right-hand sides of the constraints, and set up the starting solution in the tableau. Now, iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Determine the optimum solution by inspecting the values in the tableau."