In the Branch-And-Bound Technique for Solving Integer Linear Programming Models $\le$

In the branch-and-bound technique for solving integer linear programming models with a maximization objective function:

A) Once a feasible solution is found, it is optimal.
B) If the solution generated at one stage is X₁ = 5.7, X₂ = 3 but gives an objective function value higher than that of the best integer solution found to date, X₂ must be either 0, 1, or 2 in the optimal solution.
C) If the solution generated at one stage is X₁ = 5.7, X₂ = 3 but gives an objective function value higher than that of the best integer solution found to date, a new linear programming problem is solved with two constraints added: X₁ $\le$ 6 and X₁ $\ge$ 5.
D) If the solution generated at one stage is X₁ = 5.7, X₂ = 3 but gives an objective function value higher than that of the best integer solution found to date, two new linear programs are solved, one with the constraint