input: Write a function to explain the approach for solving a linear programming problem using the Simplex method in Python. The function should first define the problem in terms of the decision variables, objective function, and constraints. Then, it should convert the problem into standard form by introducing slack variables, if needed. Next, it should 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. The function should then iteratively use the Simplex algorithm to move from a vertex to the next until an optimum solution is reached. Finally, it should determine the optimum solution by inspecting the values in the tableau.
  assert simplex_explanation("Maximize 3x + 4y subject to 2x + y <= 10, x + 2y <= 15")==("First, define the decision variables (x, y), objective function (3x + 4y), and constraints (2x + y <= 10, x + 2y <= 15). Convert into standard form by introducing slack variables. Create a tableau and set up the initial solution. Iteratively use the Simplex method to move to the next vertex until an optimum solution is reached, which is determined by examining the tableau.")
  assert simplex_explanation("Minimize 6x - 4y subject to x + y >= 5, x - y <= 2")==("First, define the decision variables (x, y), objective function (6x - 4y), and constraints (x + y >= 5, x - y <= 2). Convert into standard form by introducing slack variables. Create a tableau and set up the initial solution. Iteratively use the Simplex method to move to the next vertex until an optimum solution is reached, which is determined by examining the tableau.")
  assert simplex_explanation("")==("")
  assert simplex_explanation("Maximize -x + y subject to x + y <= 3, -x + y <= 2")==("First, define the decision variables (x, y), objective function (-x + y), and constraints (x + y <= 3, -x + y <= 2). Convert into standard form by introducing slack variables. Create a tableau and set up the initial solution. Iteratively use the Simplex method to move to the next vertex until an optimum solution is reached, which is determined by examining the tableau.")
output: def simplex_explanation(problem_statement):
      if not problem_statement:
          return ""
      return f"First, define the decision variables (x, y), objective function ({problem_statement.split('subject to')[0].strip().replace('Maximize', '').replace('Minimize', '').strip()}), and constraints ({problem_statement.split('subject to')[1].strip()}). Convert into standard form by introducing slack variables. Create a tableau and set up the initial solution. Iteratively use the Simplex method to move to the next vertex until an optimum solution is reached, which is determined by examining the tableau."