Q.Determine the maximum value of Z=11x+7y subject to the constraints: 2x+y≤6, x≤2, x≥0, y≥0.
Concept understanding — Linear Programming Graphical Method
The Graphical Method for Linear Programming
When a linear programming problem has just two decision variables, x and y, 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 2x+3y≤100. On the xy-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 Z=ax+by 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 (0,0)) 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 x≥0, y≥0, 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 Z 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
If the feasible region is a closed polygon (bounded), both the maximum and minimum are guaranteed and are found among the corners. If the region stretches to infinity (unbounded), a maximum or minimum may fail to exist — you then check whether Z can be pushed indefinitely large or small in the open direction before concluding.
The bottom line
Graph the constraints, find the feasible region, list its corner points, and compare Z=ax+by at each. The best corner is your optimal solution — a clean, visual route to the answer for any two-variable LP problem.
The graphical method for solving linear programming problems is the entire method taught in the NCERT Class 12 Linear Programming chapter, and "linear programming graphical method examples class 12" is one of the most searched topics ahead of CBSE board exams. This corner-point approach is also occasionally tested in JEE Main and select state CET papers involving optimization.
Maximise Z=11x+7y over 2x+y≤6, x≤2, x≥0, y≥0 by testing the corner points.
Corners of the feasible region:
- (0,0)
- (2,0) — from x=2, y=0
- (2,2) — from x=2 and 2x+y=6
- (0,6) — from x=0 and 2x+y=6
Values of Z=11x+7y:
- (0,0):0
- (2,0):22
- (2,2):22+14=36
- (0,6):0+42=42
The largest is 42.
Maximum Z=42, attained at (0,6).
Testing the four corners of the feasible region, Z=11x+7y is largest at (0,6), where Z=42.
Set-up
We maximise Z=11x+7y subject to
2x+y≤6,x≤2,x≥0, y≥0.
By the corner-point theorem the maximum of a linear objective over a bounded region occurs at a vertex, so we only need the vertices.
Step 1 — Find the corner points
The boundary lines are x=0, y=0, x=2 and 2x+y=6 (intercepts (3,0),(0,6)).
- x=0,y=0⇒(0,0).
- x=2,y=0⇒(2,0).
- x=2 in 2x+y=6⇒4+y=6⇒y=2⇒(2,2).
- x=0 in 2x+y=6⇒y=6⇒(0,6).
Do not use (3,0): although 2x+y=6 meets the x-axis there, x=3 breaks x≤2, so (3,0) is outside the feasible region. The line x=2 cuts it off.
So the feasible region is the quadrilateral (0,0),(2,0),(2,2),(0,6).
Step 2 — Evaluate Z=11x+7y
| Vertex | Z=11x+7y |
|---|---|
| (0,0) | 0 |
| (2,0) | 22 |
| (2,2) | 22+14=36 |
| (0,6) | 0+42=42 |
Step 3 — Pick the best
The values are 0,22,36,42; the maximum is 42, at (0,6). Check (0,6): 2(0)+6=6≤6 and 0≤2 — feasible.
The maximum value is Z=42, attained at (0,6).
Method: Corner-Point Method when One Constraint Cuts Off a Vertex
Use this for a bounded maximisation where a simple bound (like x≤k) trims the region, so some "obvious" intersection points are actually infeasible.
Steps
Step 1: Plot all boundaries, including the cutting bound.
Draw each constraint line and the non-negativity axes. A vertical/horizontal bound such as x≤k or y≤k slices across a sloping line.
Step 2: Find candidate intersections — then keep only feasible ones.
Solve each relevant pair of lines. Crucially, an axis-intercept of a sloping line (e.g. where 2x+y=6 meets the x-axis) may lie outside the region because it violates the cutting bound. Discard any intersection that breaks any constraint.
Step 3: Evaluate Z=ax+by at the surviving corners.
Tabulate Z at each genuine vertex of the trimmed polygon and select the optimum.
The most common slip here is using the full line's intercept as a corner. Always re-check each candidate against every constraint before treating it as a vertex — the cutting bound is exactly what makes some intercepts invalid.
Common Mistakes
Mistake 1: Using (3,0) as a corner.
Why it's wrong: the line 2x+y=6 meets the x-axis at (3,0), but x=3 violates x≤2, so (3,0) is outside the feasible region. Correct approach: the bound x≤2 cuts the region — the true corner on that edge is (2,2), from x=2 in 2x+y=6.
Mistake 2: Not testing every candidate against all constraints.
Why it's wrong: an intersection of two lines can still break a third constraint and so not be a real vertex. Correct approach: check each candidate corner against 2x+y≤6, x≤2, x≥0, y≥0 before evaluating Z=11x+7y.
- JKBOSE Class 12 Annual Regular Examination 2022Set SZ2 marksQ.Solve the following L.P.P. graphically : Maximise : Z=3x+4y. Subject to constraints : x+y≤4, x≥0, y≥0.
›Reveal solutionSolution
The feasible region is a triangle with corners (0,0),(4,0),(0,4); evaluating Z=3x+4y at each shows the maximum is 16 at (0,4).
Constraints: x+y≤4, x≥0, y≥0.
This describes the triangular region in the first quadrant bounded by the line x+y=4 and the axes, with corner (vertex) points:
(0,0),(4,0),(0,4).
By the Fundamental Theorem of Linear Programming, the maximum of a linear objective function over a bounded feasible region occurs at a corner point. Evaluate Z=3x+4y at each:
Corner Z=3x+4y (0,0) 0 (4,0) 12 (0,4) 16 The largest value is 16, at (0,4).
✓Final answerMaximum value of Z is 16, attained at (x,y)=(0,4).
- JKBOSE Class 12 Annual Regular Examination 2020Set SZ2 marksQ.Shade the feasible region of L.P.P. x+3y≥3, x+y≥2, x,y≥0.
›Reveal solutionSolution
Plot both boundary lines, test the origin to pick the correct side, and shade the intersection with the first quadrant.
This question asks for a hand-drawn shaded graph, which cannot be rendered here — the region is described numerically instead.
Constraints: x+3y≥3, x+y≥2, x,y≥0.
x+3y=3 passes through (3,0) and (0,1). x+y=2 passes through (2,0) and (0,2).
Testing the origin (0,0) in each: 0≥3 is false and 0≥2 is false, so the origin is NOT in the feasible region — shade the side of each line away from the origin.
Intersection of the two lines: from x+y=2, x=2−y; substitute into x+3y=3: (2−y)+3y=3⇒2y=1⇒y=21, x=23.
The feasible region is unbounded, lying above/right of both lines in the first quadrant, with vertices (0,2) (on the y-axis, where x+y=2 dominates), (23,21) (intersection of the two lines), and (3,0) (on the x-axis, where x+3y=3 dominates) — extending outward to infinity beyond (0,2) along the y-axis side and beyond (3,0) along the x-axis side.
✓Final answerFeasible region: unbounded, above/right of both lines, first quadrant, with corner points (0,2), (23,21), (3,0).
- JKBOSE Class 12 Annual Regular Examination 2018Set WZ2 marksQ.Minimize Z=3x+2y subject to the constraints x+y≥8, x,y≥0.
›Reveal solutionSolution
The feasible region's corners on the boundary line x+y=8 are (8,0) and (0,8); comparing Z=3x+2y at each (and checking the unbounded direction) gives the minimum at (0,8).
Minimize Z=3x+2y subject to x+y≥8, x,y≥0.
Corner points: the boundary line x+y=8 meets the axes at (8,0) and (0,8); the feasible region is everything on or above this line in the first quadrant (unbounded).
Z(8,0)=24,Z(0,8)=16
Parametrizing the boundary as x=t, y=8−t for t∈[0,8]: Z=3t+2(8−t)=t+16, which is smallest at t=0, i.e. at (0,8), giving Z=16.
Moving further into the interior of the feasible region (away from the boundary line, e.g. increasing x or y beyond the line) only increases Z since both coefficients 3 and 2 are positive. So the minimum occurs on the boundary at (0,8).
✓Final answerMinimum value of Z=3x+2y is 16, attained at x=0, y=8.
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