In graphical solution, a feasible solution is any solution to an LPP which satisfies-
A. only objective function
B. non-negativity restriction
C. only constraint
D. All of the above

Hint: The general methods of solving an LPP and its theory will be applied in the problem. Linear programming or mathematical modeling is a technique in which a linear function is maximized or minimized when subjected to various constraints. We will check each option one by one to see which is satisfied by a feasible solution.

Complete step-by-step answer:

We will start by defining what a feasible solution is. The feasible region is the set of all the points that satisfy all the given constraints.

Also, we know that the variables of the linear programs must always take the non-negative values. This is followed because x and y are usually the number of items produced or the cost of a production and we cannot produce a negative number of items. The least possible number of items could be zero.

Now, we will check each option if it satisfies the condition or not. The first option is that a feasible solution only satisfies an objective function. Clearly, this is wrong as we have no such condition.
Option B says that the non-negativity restriction is satisfied by a feasible solution, which is true, because we already know that the variables cannot be negative. Finally, option C says that it satisfies only the constraints, which is wrong because they satisfy the non-negativity restriction as well.
 Hence, the correct option is B.

Note: In such types of questions, it is important to know the meaning and every term written in the question. Most of the time, students are not able to understand the language of the question, which often leads to the wrong answer. Hence, students should always thoroughly go through the theoretical aspect of each and every topic.