Q.Refer to Exercise 12. What will be the minimum cost?
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The Graphical Method for Linear Programming
When a linear programming problem has just two decision variables, and , you can solve it by drawing a picture. This is the graphical method, and it is the technique the CBSE Class-12 course expects you to use.
The idea
Each constraint is a linear inequality such as . On the -plane its boundary is a straight line, and the inequality picks one side of that line (a half-plane). The points that satisfy all the constraints at once form a single region — the feasible region. Your job is to find the point inside this region that makes the objective function largest or smallest.
The step-by-step procedure
- Draw each constraint line. Replace every inequality by an equation and plot the line, usually by finding where it meets the axes.
- Shade the correct side. Test a simple point (often the origin ) in the inequality. If it holds, the origin's side is the wanted half-plane; if not, take the other side. Always include the non-negativity conditions , which keep you in the first quadrant.
- Identify the feasible region. It is the overlap of all the shaded half-planes — the region satisfying every constraint together.
- Find the corner (vertex) points. These are the points where the boundary lines cross. Read them off the graph or solve the two relevant lines simultaneously.
- Evaluate at every corner and pick the largest value (for a maximum) or the smallest (for a minimum).
The whole method rests on the Corner-Point Theorem: if an optimum exists, it occurs at a vertex of the feasible region. So you never test interior points — only the corners.
Bounded vs unbounded …
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