A set of values of decision variables which satisfies the linear constraint and non-negativity condition of linear programming problem is called

feasible solution

The correct answer is (3) feasible solution.

In linear programming, a feasible solution is a set of values for the decision variables that satisfies all the given linear constraints and also satisfies the non-negativity conditions (i.e., each decision variable must be greater than or equal to zero). Feasible solutions form the feasible region, and the goal of linear programming is to find the optimal solution, often the one that maximizes or minimizes the objective function while staying within the feasible region.