Q.Find the value of the following: Maximise Z=3x+4y subject to the constraints : x+y≤4,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.
The key idea is that the maximum of a linear objective under linear constraints occurs at a corner point of the feasible region.
Step 1 – Feasible region
The constraints x+y≤4, x≥0, y≥0 define a right triangle with vertices at (0,0), (4,0), and (0,4).
Step 2 – Evaluate Z at each corner
- At (0,0): Z=3(0)+4(0)=0
- At (4,0): Z=3(4)+4(0)=12
- At (0,4): Z=3(0)+4(4)=16
Step 3 – Compare
The largest value is 16 at (0,4).
The maximum value is 16.
This is a linear programming problem where we maximise Z=3x+4y under x+y≤4, x≥0, y≥0. The feasible region is a right triangle with vertices at (0,0), (4,0), and (0,4). The maximum value of Z is 16, achieved at (0,4).
The core idea here is that in linear programming, the maximum (or minimum) of a linear objective function under linear constraints always occurs at a corner point of the feasible region — provided the region is bounded. This is the corner point theorem. So instead of checking every possible point (which is infinite), we only need to examine the vertices of the region formed by the constraints.
Let’s build the feasible region step by step.
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Plot the constraints.
The inequality x+y≤4 describes all points on or below the line x+y=4.
The conditions x≥0 and y≥0 restrict us to the first quadrant.
So the feasible region is the triangle with vertices at (0,0), (4,0), and (0,4).
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Identify the corner points.
These are the intersections of the boundary lines:
- Intersection of x=0 and y=0: (0,0)
- Intersection of y=0 and x+y=4: (4,0)
- Intersection of x=0 and x+y=4: (0,4)
There is no fourth corner because the line x+y=4 meets the axes exactly at these two points.
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Evaluate the objective function at each corner.
Z=3x+4y:
- At (0,0): Z=3(0)+4(0)=0
- At (4,0): Z=3(4)+4(0)=12
- At (0,4): Z=3(0)+4(4)=16
-
Compare the values.
The largest is 16 at (0,4).
A common mistake is to assume the maximum occurs where x is largest, because 3x seems significant. But here 4y grows faster per unit, so the optimum shifts to the y-axis. Always check all corners — don’t guess.
Notice that the objective function’s slope is −43, which is shallower than the constraint line’s slope of −1. This means the maximum will be on the y-axis rather than the x-axis. A quick slope comparison can save time in multiple-choice exams.
The maximum value is 16, attained at the point (0,4).
Method: Graphical Corner-Point Method (Bounded Maximisation)
The standard route for maximising a linear objective Z=ax+by subject to two-variable linear constraints.
Steps
Step 1: Plot each constraint line.
Replace every inequality by an equation and draw the line, usually via its axis intercepts. Include the non-negativity lines x=0 and y=0.
Step 2: Shade the correct half-plane and find the feasible region.
Test the origin in each inequality: if it holds, keep the origin's side; otherwise the other. The feasible region is the overlap of all the kept half-planes — for constraints like x+y≤c with x,y≥0 it is a closed polygon in the first quadrant.
Step 3: Read off the corner points.
The vertices are where boundary lines cross — solve the relevant pairs of equations (or read them from the graph).
Step 4: Evaluate Z at every corner and pick the best.
By the Corner-Point Theorem the maximum sits at a vertex, so tabulate Z=ax+by at each and take the largest.
Comparing slopes helps: if the objective line is shallower or steeper than a boundary edge, the optimum shifts toward the axis that the objective "prefers" — but always confirm by evaluating the corners.
Common Mistakes
Mistake 1: Assuming the maximum is where x is largest.
Why it's wrong: (4,0) gives Z=12, but (0,4) gives Z=3(0)+4(4)=16 — larger, because y's coefficient (4) beats x's (3). Correct approach: evaluate Z=3x+4y at all three corners (0,0),(4,0),(0,4) and take the biggest.
Mistake 2: Forgetting the origin as a corner.
Why it's wrong: skipping (0,0) can lose the minimum (and, in other problems, the maximum). Correct approach: list every vertex of the triangle, including the origin, before evaluating.
Showing the 12 most recent of 28 on this concept.
- CBSE 2026Set 65/2/11 markMCQQ.For the feasible region shown below, the non-trivial constraints of the linear programming problem are (A) x+y≤5, x+3y≤9 (B) x+y≤5, x+3y≥9 (C) x+y≥5, x+3y≤9 (D) x+y≥5, 3x+y≤9
›Reveal solutionSolution
The feasible region is bounded by two lines that form its upper boundary. By checking which inequalities produce the shaded area (the region below both lines), the correct constraints are x+y≤5 and x+3y≤9, which is option (A).
In Linear Programming, the graphical method works because each linear constraint cuts the plane into two half-planes — one where the inequality holds, one where it doesn’t. The feasible region is the intersection of all such half-planes. When you’re given a picture of the region, the trick is to identify which side of each boundary line is shaded.
The two lines visible in the diagram are:
- x+y=5 (passing through (5,0) and (0,5))
- x+3y=9 (passing through (9,0) and (0,3))
The feasible region is the pentagon-shaped area that lies below both of these lines (since the origin (0,0) is inside the region, and it satisfies 0≤5 and 0≤9). That means the inequalities must be of the “less than or equal to” type.
Let’s check each option:
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Option (A): x+y≤5, x+3y≤9
The origin satisfies both. The shaded region is below both lines — matches the diagram.
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Option (B): x+y≤5, x+3y≥9
The origin fails the second inequality (0≥9 is false). So the region would not include the origin — contradicts the diagram.
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Option (C): x+y≥5, x+3y≤9
The origin fails the first inequality (0≥5 is false). Again, the origin would be excluded — not the case.
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Option (D): x+y≥5, 3x+y≤9
The origin fails the first inequality. Also, the second line here is 3x+y=9, which is different from the line in the diagram (the diagram has x+3y=9, not 3x+y=9). So this is doubly wrong.
Watch outA common mistake is to confuse x+3y≤9 with 3x+y≤9. They are different lines — swapping coefficients changes the slope entirely. Always check which line actually appears in the diagram.
TipWhen the feasible region contains the origin, all constraints must be of the form ax+by≤c (with c≥0), because the origin gives 0≤c. If the origin is outside, at least one constraint will be ≥.
✓Final answerThe correct option is (A).
- CBSE 2026Set A1 markMCQQ.The maximum value of Z=4x+y subject to the constraints x+y≤50, x≥0, y≥0 is(a) 50(b) 250(c) 0(d) none of these
›Reveal solutionSolution
Evaluate Z at the corner points; the maximum is 200, not listed.
The feasible region has corner points (0,0), (50,0), (0,50).
- Z(0,0)=0
- Z(50,0)=4(50)+0=200
- Z(0,50)=4(0)+50=50
The maximum value is 200, attained at (50,0). Since 200 is not among 50, 250 or 0, the answer is "none of these".
✓Final answer(d) none of these — maximum Z=200 at (50,0).
- CBSE 2026Set ANNUAL1 markMCQQ.What is the maximum value of Z=3x+4y subject to the constraints x+y≤4, x≥0 and y≥0?(a) 12(b) 14(c) 16(d) 19
›Reveal solutionSolution
Evaluating Z=3x+4y at the corner points of the feasible region gives a maximum of 16 at (0,4).
The constraints are x+y≤4, x≥0, y≥0. This describes a triangular feasible region with corner points where the boundary lines meet:
- Intersection of x=0 and y=0: (0,0)
- Intersection of x+y=4 and y=0: (4,0)
- Intersection of x+y=4 and x=0: (0,4)
By the Corner Point Theorem, the maximum (or minimum) of a linear objective function over a bounded feasible region occurs at one of the corner points. Evaluate Z=3x+4y at each:
Corner point Z=3x+4y (0,0) 0 (4,0) 12 (0,4) 16 The maximum value is 16, attained at (0,4).
✓Final answerThe correct option is (c) 16.
- CBSE 2026Set ANNUAL1 markMCQQ.The maximum value of the objective function Z = 3x + 4y under the constraints x + y \le 1, x \ge 0, y \ge 0 will be:(a) 4(b) 5(c) 0(d) 6
›Reveal solutionSolution
By the corner-point method, evaluate Z=3x+4y at each vertex of the feasible region and pick the largest.
Feasible region: x+y≤1, x≥0, y≥0 is the triangle with vertices (0,0), (1,0), (0,1).
Evaluate Z=3x+4y at each corner (Fundamental Theorem of LPP — the optimum of a linear objective over a bounded feasible region occurs at a corner point):
- (0,0): Z=0
- (1,0): Z=3
- (0,1): Z=4
The largest value is 4.
✓Final answerMaximum value of Z is 4, at the corner point (0,1) — option (a).
- CBSE 2025Set 65/2/11 markMCQQ.A factory produces two products X and Y. The profit earned by selling X and Y is represented by the objective function Z=5x+7y, where x and y are the number of units of X and Y respectively sold. Which of the following statement is correct? (A) The objective function maximizes the difference of the profit earned from products X and Y. (B) The objective function measures the total production of products X and Y. (C) The objective function maximizes the combined profit earned from selling X and Y. (D) The objective function ensures the company produces more of product X than product Y.
›Reveal solutionSolution
The objective function Z=5x+7y is a linear combination of the number of units sold, where the coefficients (5 and 7) are the per-unit profits. Therefore, Z represents the total profit from selling both products, and the goal is to maximize this combined profit. The correct option is (C).
The core idea here is what an objective function means in linear programming. In any optimization problem — whether it's profit, cost, distance, or time — the objective function is a single mathematical expression that quantifies what you want to make as large (or as small) as possible.
Here, the function is Z=5x+7y.
The variables x and y stand for the number of units of product X and product Y that are sold. The numbers 5 and 7 are the profit per unit of X and Y respectively. So:
- If you sell one unit of X, you add ₹5 to Z.
- If you sell one unit of Y, you add ₹7 to Z.
That means Z is simply the total profit from all units sold:
Z=(profit per unit of X)×(units of X)+(profit per unit of Y)×(units of Y).
Now, in a typical linear programming problem, you are asked to maximize or minimize this Z subject to some constraints (like limited raw materials, labour, or demand). The question here doesn't give constraints — it only asks what the objective function itself represents.
Let’s examine each option:
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Option (A) says the objective function maximizes the difference of the profits from X and Y.
That would look like 5x−7y or 7y−5x — a subtraction. But here we have addition, so this is wrong.
-
Option (B) says it measures the total production (i.e., total number of units).
Total production would be x+y (just adding the counts, ignoring profit). But here each unit is weighted by its profit, so Z is not the count — it’s the profit.
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Option (C) says it maximizes the combined profit from selling X and Y.
This is exactly right. Z adds up the profit contributions from both products, and the goal is to make this total as large as possible.
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Option (D) says it ensures the company produces more of X than Y.
The objective function itself doesn’t enforce any inequality between x and y. It just sums profits. Any such condition would come from constraints, not from Z.
Watch outA common mistake is to think the coefficients (5 and 7) represent the number of units or the price rather than the profit per unit. Always check: in a profit maximization problem, the coefficient of each variable is the per-unit profit.
TipIf you ever forget, just plug in a simple mental example: suppose x=1 and y=1. Then Z=5(1)+7(1)=12. That’s clearly the total profit from one unit of each, not the difference, not the count, and not a comparison.
✓Final answerThe correct option is (C) — the objective function maximizes the combined profit earned from selling X and Y.
- CBSE 2025Set 65/4/11 markMCQQ.The corner points of the feasible region of a Linear Programming Problem are (0,2), (3,0), (6,0), (6,8) and (0,5). If Z=ax+by; (a,b>0) be the objective function, and maximum value of Z is obtained at (0,2) and (3,0), then the relation between a and b is : (A) a=b (B) a=3b (C) b=6a (D) 3a=2b
›Reveal solutionSolution
In a linear programming problem, if the maximum occurs at two distinct corner points, the objective function is constant along the edge joining them. Here, the maximum at (0,2) and (3,0) forces 2a=3b, so the correct relation is 3a=2b, which is option (D).
The key idea in the graphical method of linear programming is that the optimal value of a linear objective function Z=ax+by (with a,b>0) over a convex feasible region always occurs at a corner point. If it occurs at two different corner points, then every point on the line segment joining them also gives the same optimal value — the objective function is constant along that edge.
Here, the maximum occurs at both (0,2) and (3,0). That means Z has the same value at these two points. Let's work through the reasoning step by step.
-
Write the objective function at each given point.
At (0,2): Z=a(0)+b(2)=2b.
At (3,0): Z=a(3)+b(0)=3a.
-
Since both give the same maximum value, we equate them:
2b=3a
- Rearrange to find the relation between a and b. From 2b=3a, we get 3a=2b. This is a direct linear relation.
Watch outA common mistake is to stop at 2b=3a and pick an option like a=3b or b=6a by misreading the equation. Always check: 2b=3a means b=23a, not b=3a or a=3b. The correct form matching the options is 3a=2b.
- Verify against the options.
Option (D) is 3a=2b, which matches exactly. The other options would give different ratios:
- (A) a=b would mean 2b=2a, not 3a.
- (B) a=3b would give 2b=9b, impossible unless b=0.
- (C) b=6a would give 12a=3a, also impossible.
TipWhen a linear programming problem says the maximum occurs at two corner points, you don't need to check all points — just equate the objective values at those two points. The edge between them is a line of constant Z, and that single equation gives the required relation.
✓Final answerThe correct relation is 3a=2b, which corresponds to option (D).
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- CBSE 2025Set E1 markMCQQ.The maximum value of Z=2x+y subject to constraints x+y≤35, x≥0, y≥0 is(a) 35(b) 105(c) 70(d) 140
›Reveal solutionSolution
Evaluate Z at the corner points of the feasible region; the maximum is 70.
The feasible region defined by x+y≤35, x≥0, y≥0 is a triangle with corner points (0,0), (35,0) and (0,35).
Evaluate Z=2x+y:
- At (0,0): Z=0
- At (35,0): Z=2(35)+0=70
- At (0,35): Z=0+35=35
The largest value is 70.
✓Final answer(C) 70.
- CBSE 2025Set E1 markMCQQ.The maximum value of Z=3x−y subject to constraints x+y≤8, x≥0, y≥0 is(a) −8(b) 24(c) 16(d) 8
›Reveal solutionSolution
Evaluate Z=3x−y at the corner points; the largest value is 24 at (8,0).
The feasible region for x+y≤8, x≥0, y≥0 is a triangle with corner points (0,0), (8,0), (0,8). Evaluate Z=3x−y:
- (0,0):Z=0
- (8,0):Z=24
- (0,8):Z=−8
The maximum is 24.
✓Final answer(B) 24.
- CBSE 2025Set ANNUAL1 markMCQQ.What is the minimum value of 2x+y subject to x+2y≥6, x≥0, y≥0?(i) 3(ii) 5(iii) 6(iv) 0
›Reveal solutionSolution
Evaluate the objective function at the corner points of the (unbounded) feasible region.
The feasible region for x+2y≥6, x≥0, y≥0 has corner points where the boundary line x+2y=6 meets the axes: (6,0) and (0,3) (the region extends unboundedly away from the origin beyond these).
For a minimisation problem with an unbounded region of this "≥" type, the minimum (if it exists) occurs at a corner point:
- At (6,0): Z=2(6)+0=12
- At (0,3): Z=2(0)+3=3
The minimum value is Z=3, attained at (0,3).
✓Final answer(i) 3, at the point (0,3).
- CBSE 2025Set ANNUAL1 markMCQQ.The maximum value of the objective function Z=3x+4y subject to the constraints x≥0, y≥0 and x+y≤1 is(a) 7(b) 4(c) 3(d) 10
›Reveal solutionSolution
Evaluate Z at each corner of the triangular feasible region and pick the largest.
The constraints x≥0, y≥0, x+y≤1 define a triangle with vertices
(0,0),(1,0),(0,1).
Evaluate Z=3x+4y at each corner:
Z(0,0)=3(0)+4(0)=0,
Z(1,0)=3(1)+4(0)=3,
Z(0,1)=3(0)+4(1)=4.
The greatest value is 4, attained at (0,1).
Checking the options: (a) 7 and (d) 10 exceed anything the region allows; (c) 3 is only the value at (1,0); the maximum is (b) 4.
✓Final answer(b) 4 (attained at (0,1))
- CBSE 2024Set 65/3/11 markMCQQ.Of the following, which group of constraints represents the feasible region given below (shown in the figure of the question paper)? (A) x+2y≤76, 2x+y≥104, x,y≥0 (B) x+2y≤76, 2x+y≤104, x,y≥0 (C) x+2y≥76, 2x+y≤104, x,y≥0 (D) x+2y≥76, 2x+y≥104, x,y≥0
›Reveal solutionSolution
The problem asks us to identify the set of linear inequalities that define a given feasible region in a graph. By finding the equations of the boundary lines and testing a point (like the origin) to determine the correct inequality direction, we find the constraints are x+2y≤76, 2x+y≤104, x≥0, and y≥0. The correct option is (B).
In Linear Programming, a "feasible region" is the set of all points (x,y) that satisfy all the given constraints simultaneously. Each linear inequality defines a half-plane, and the feasible region is the intersection of these half-planes. When given a graph of a feasible region, we need to reverse this process: identify the boundary lines, find their equations, and then determine the correct inequality sign (≤ or ≥) for each line based on which side of the line the feasible region lies.
Here's how we can determine the constraints from the given figure:
-
Identify the boundary lines and their intercepts.
The figure shows a feasible region bounded by two lines in the first quadrant. This immediately tells us that the non-negativity constraints x≥0 and y≥0 are part of the group.
Let's identify the intercepts of the two main lines from the figure:
- Line 1: This line intersects the x-axis at (76,0) and the y-axis at (0,38).
- Line 2: This line intersects the x-axis at (52,0) and the y-axis at (0,104).
-
Determine the equation for each line.
We can use the intercept form of a linear equation, ax+by=1, where a is the x-intercept and b is the y-intercept.
- For Line 1 (intercepts (76,0) and (0,38)):
76x+38y=1
To clear the denominators, multiply the entire equation by the least common multiple of $76$ and $38$, which is $76$:76(76x)+76(38y)=76(1)
x+2y=76
* **For Line 2 (intercepts $(52, 0)$ and $(0, 104)$):**52x+104y=1
To clear the denominators, multiply the entire equation by the least common multiple of $52$ and $104$, which is $104$:104(52x)+104(104y)=104(1)
2x+y=104
-
Determine the inequality for each line.
The feasible region is the shaded area. We need to determine if the region satisfies ≤ or ≥ for each line. A common method is to pick a test point that is clearly inside the feasible region (or clearly outside) and substitute its coordinates into the line's equation. The origin (0,0) is usually the easiest test point, provided it does not lie on the line itself. In this case, the origin (0,0) is clearly part of the feasible region.
-
For the line x+2y=76:
Test the origin (0,0):
Substitute x=0,y=0 into x+2y:
0+2(0)=0.
Since the origin (0,0) is within the feasible region, the inequality must hold true for (0,0). Comparing 0 with 76, we need 0≤76.
Therefore, the inequality for this line is x+2y≤76.
-
For the line 2x+y=104:
Test the origin (0,0):
Substitute x=0,y=0 into 2x+y:
2(0)+0=0.
Since the origin (0,0) is within the feasible region, the inequality must hold true for (0,0). Comparing 0 with 104, we need 0≤104.
Therefore, the inequality for this line is 2x+y≤104.
TipIf the feasible region is on the side of the line that includes the origin, the inequality will typically be ≤ (assuming the constant term is positive). If it's on the side opposite to the origin, it will typically be ≥. This is a quick check, but always verify with a test point.
-
-
Combine all constraints.
Based on our analysis, the constraints that define the feasible region are:
- x+2y≤76
- 2x+y≤104
- x≥0 (because the region is in the first quadrant, to the right of the y-axis)
- y≥0 (because the region is in the first quadrant, above the x-axis)
-
Compare with the given options.
Let's check which option matches our derived constraints:
(A) x+2y≤76, 2x+y≥104, x,y≥0
(B) x+2y≤76, 2x+y≤104, x,y≥0
(C) x+2y≥76, 2x+y≤104, x,y≥0
(D) x+2y≥76, 2x+y≥104, x,y≥0
Our derived constraints match option (B).
✓Final answerThe group of constraints representing the feasible region is (B).
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- CBSE 2024Set D1 markMCQQ.The minimum value of Z=3x+5y subject to the constraints where x+y≤2, x≥0, y≥0 is(a) 16(b) 15(c) 0(d) none of these
›Reveal solutionSolution
The feasible region includes the origin, where Z=0 is the minimum.
The constraints x+y≤2, x≥0, y≥0 form a triangle with corner points (0,0),(2,0),(0,2). Evaluate Z=3x+5y: at (0,0), Z=0; at (2,0), Z=6; at (0,2), Z=10. The minimum is 0 (at the origin).
✓Final answer(C) 0
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