Solving an integer programming problem by rounding off answers obtained by solving it as a linear programming problem (using Simplex LP), we find thatGroup of answer choicesThe values of decision variables obtained by rounding off are always very close to the optimal values.The value of the objective function for a maximization problem will likely be less than that for the Simplex LP solution.The value of the objective function for a minimization problem will likely be less than that for the Simplex LP solution.All constraints are satisfied exactly.

The correct answer is: The value of the objective function for a maximization problem will likely be less than that for the Simplex LP solution.

Here's why:

1. When you solve an integer programming problem as a linear programming problem using the Simplex method, you get a solution that is optimal for the LP problem, not necessarily for the original IP problem.

2. If the problem is a maximization problem, the LP solution provides an upper bound for the IP problem. This is because the LP solution allows for fractional values, which can lead to a higher objective function value than integer values.

3. When you round off the LP solution to get an integer solution, you are likely to decrease the value of the objective function. This is because you are moving away from the optimal LP solution towards a potentially less optimal IP solution.

4. Therefore, the value of the objective function for a maximization problem will likely be less than that for the Simplex LP solution.

5. The other options are not necessarily true. Rounding off does not guarantee that the values of the decision variables will be close to the optimal values, nor does it guarantee that all constraints will be satisfied exactly. And for a minimization problem, rounding off could actually lead to a higher, not lower, objective function value.