The constraints of the problems are x ≥ 0, y ≥ 0, 3x+5y ≤ 15, 5x+2y ≤ 10. The optimal solution for the constraints above is equal to
To find the optimal solution, we need the objective function. We can find the feasible region without knowing the objective function, because it is determined by the constraints alone.
If we plot the common region for the constraints x ≥ 0, y ≥ 0, 3x+5y ≤ 15, 5x+2y ≤ 10, we get the following shaded region.How does theorem 1 help in finding optimal solution when we don’t even know the objective function? Let’s see what theorem 1 says.
Let R be the feasible region (convex polygon) for a linear programming problem and let Z = ax + by be the objective function. When Z has an optimal value (maximum or minimum), where the variables x and y are subject to constraints described by linear inequalities, this optimal value must occur at a corner point (vertex) of the feasible region.
It means for the given problem, O or A or B or C is the optimal solution, since they are the corner points(figure).
So the answer is (2019,4519)