2) At the optimal solution to a linear programming problem, how many of the constraints will be satisfied? a. All of them b. At least half of them, but not all c. At least one of them, but less than half d. Exactly one (i) True or False: a. A shadow price cannot be negative because it represents the amount that the objective function value improves by for a unit increase the right-hand side of a constraint. b. The optimal value of a linear programming problem can sometimes be achieved with different variable values. c. The non-negativity constraints in linear programming models ensure that the optimal objective function value is non-negative