Q.Find the value of the following: Minimise Z=−3x+4y subject to x+2y≤8, 3x+2y≤12, 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.
Concept: Linear Programming — Minimisation with non-negative constraints.
We minimise Z=−3x+4y under the given constraints.
Step 1 – Plot the feasible region
Constraints:
x+2y≤8
3x+2y≤12
x≥0,y≥0
Step 2 – Find corner points
Intersection of x+2y=8 and 3x+2y=12: subtract to get 2x=4⇒x=2, then y=3.
Other corners: (0,0), (4,0) (from 3x+2y=12 with y=0), (0,4) (from x+2y=8 with x=0).
Step 3 – Evaluate Z at each corner
(0,0):Z=0
(4,0):Z=−12
(0,4):Z=16
(2,3):Z=−6+12=6
The minimum value is −12 at (4,0).
The minimum value is −12.
This is a linear programming problem where we minimise Z=−3x+4y under given constraints. The feasible region is bounded, and the minimum occurs at a corner point. The optimal value is Z=−12 at (4,0).
Why This Approach Works
Linear programming problems with two variables are solved graphically. The constraints define a polygon (the feasible region) in the xy-plane. The objective function Z=−3x+4y is linear, so its extreme values (minimum and maximum) must occur at the vertices (corner points) of this polygon — not in the interior. This is the corner point theorem.
Here, the coefficient of x is negative (−3), so making x large reduces Z. The coefficient of y is positive (+4), so increasing y increases Z. To minimise Z, we want x as large as possible and y as small as possible, within the constraints.
Step-by-Step Solution
1. Write down the constraints clearly
We have:
- x+2y≤8
- 3x+2y≤12
- x≥0, y≥0
These are all linear inequalities. The non-negativity constraints (x≥0, y≥0) restrict us to the first quadrant.
2. Find the boundary lines and their intersection points
Convert each inequality to an equation to find the lines:
- Line 1: x+2y=8
- Line 2: 3x+2y=12
Find where each line meets the axes:
- For Line 1: when x=0, 2y=8⇒y=4; when y=0, x=8. So points: (0,4) and (8,0).
- For Line 2: when x=0, 2y=12⇒y=6; when y=0, 3x=12⇒x=4. So points: (0,6) and (4,0).
Now find the intersection of the two lines:
{x+2y=83x+2y=12
Subtract the first equation from the second:
(3x+2y)−(x+2y)=12−8⟹2x=4⟹x=2
Substitute x=2 into x+2y=8:
2+2y=8⟹2y=6⟹y=3
So the intersection point is (2,3).
3. Identify the feasible region
The feasible region is the set of points satisfying all constraints. Since both inequalities are "≤", the region lies below both lines (and in the first quadrant). The corner points of this polygon are:
- (0,0) — origin
- (4,0) — from Line 2 on the x-axis
- (0,4) — from Line 1 on the y-axis
- (2,3) — intersection of the two lines
A common mistake is to include (0,6) as a corner point. But (0,6) lies on Line 2, yet it does not satisfy x+2y≤8 because 0+2(6)=12>8. So it is outside the feasible region. Always check every candidate point against all constraints.
4. Evaluate the objective function at each corner point
We compute Z=−3x+4y at each point:
| Corner Point | Z=−3x+4y |
|---|---|
| (0,0) | 0 |
| (4,0) | −3(4)+4(0)=−12 |
| (0,4) | −3(0)+4(4)=16 |
| (2,3) | −3(2)+4(3)=−6+12=6 |
5. Determine the minimum
The smallest value among these is −12 at (4,0). Since the feasible region is bounded (a closed polygon), this is the global minimum.
Notice that Z decreases as x increases (because of −3x) and increases as y increases. The point (4,0) has the largest x and smallest y among all corner points — exactly what we expected intuitively.
The minimum value is −12 at the point (4,0).
Method: Solving a two-variable LPP graphically (minimisation)
This is the full graphical corner-point method — the technique behind every "linear programming problems class 12 with solutions" question. Here the objective mixes a negative and a positive coefficient.
Steps
Step 1: Draw each constraint line and shade its half-plane.
Replace every inequality by an equation, plot via axis intercepts, and test the origin to pick the correct side. The non-negativity conditions x≥0, y≥0 keep you in the first quadrant.
Step 2: Identify the feasible region and its true corners.
Corners are intersections of boundary lines that satisfy all constraints — discard any intersection that violates even one inequality.
Step 3: Evaluate and minimise.
Z=ax+by
Compute Z at every valid corner and take the smallest. With a negative x-coefficient, expect the minimum where x is largest and y smallest — a useful check on the arithmetic. A bounded region guarantees this minimum is global.
Common Mistakes
Mistake 1: Accepting an axis intercept without checking the other constraint.
Why it's wrong: (0,6) lies on 3x+2y=12 but fails x+2y≤8, so it is not a corner. Correct approach: test every candidate against all constraints before treating it as a vertex.
Mistake 2: Mishandling the −3x term.
Why it's wrong: forgetting the minus sign makes (4,0) look like a large positive value instead of −12. Correct approach: a larger x decreases Z=−3x+4y, so the minimum is at the largest-x, smallest-y corner, (4,0).
- AHSEC Higher Secondary (HS) Final Examination 2026Set ANNUAL6 marksQ.Solve the following linear programming problem graphically : Minimize Z=10(x−7y+190) subject to the constraints x+y≤8, x≤5, y≤5, x+y≥4, x≥0, y≥0.
›Reveal solutionSolution
Main: min Z=1550 at (0,5). OR: Z=−50x+20y is unbounded below on the feasible region, so no minimum exists.
Main part. Constraints: x+y≤8, x≤5, y≤5, x+y≥4, x,y≥0. This is a bounded region with corner points (0,4),(0,5),(3,5),(5,3),(5,0),(4,0). Evaluate Z=10(x−7y+190):
- (0,4): 10(0−28+190)=1620
- (0,5): 10(0−35+190)=1550
- (3,5): 10(3−35+190)=1580
- (5,3): 10(5−21+190)=1740
- (5,0): 10(5−0+190)=1950
- (4,0): 10(4−0+190)=1940
The minimum is Z=1550 at (0,5).
OR part. Minimize Z=−50x+20y subject to 2x−y≥−5, 3x+y≥3, 2x−3y≤12, x,y≥0. Corner points are (0,3),(0,5),(1,0),(6,0), with Z=60,100,−50,−300 respectively; the smallest corner value is −300 at (6,0). But the feasible region is unbounded (it extends without bound as x increases). Testing the open half-plane −50x+20y<−300: along the edge 2x−3y=12, writing x=6+23y gives Z=−50(6+23y)+20y=−300−55y, which decreases without limit as y→∞ while all constraints stay satisfied. Hence −300 is not a minimum, and Z has no minimum value.
✓Final answerMain: minimum Z=1550 at (0,5). (OR: Z=−50x+20y has no minimum value, since the feasible region is unbounded and Z is unbounded below.)
- AHSEC Higher Secondary (HS) Final Examination 2025Set ANNUAL6 marksQ.Solve graphically the following linear programming problem: Maximize and minimize Z=3x+5y subject to the constraints 2x+3y≤36, x+y≤15, y≥3, x≥0. OR Determine graphically the minimum value of the objective function Z=3x+9y subject to the constraints x+3y≤60, x+y≥10, x≤y, x≥0, y≥0.
›Reveal solutionSolution
Main: plot the constraints, find corner points of the feasible region, evaluate Z at each — max and min occur at corner points (corner-point theorem). OR: same method for a different feasible region and objective.
Main: Maximize/minimize Z=3x+5y subject to 2x+3y≤36, x+y≤15, y≥3, x≥0 (with y≥0 implicit).
Find the corner points of the feasible region by intersecting boundary lines:
- x=0 and y=3: (0,3)
- x=0 and 2x+3y=36: y=12, point (0,12)
- y=3 and x+y=15: x=12, point (12,3) [note: y=3 meeting 2x+3y=36 gives x=13.5, but that violates x+y≤15, so it is not a feasible vertex]
- x+y=15 and 2x+3y=36: substituting x=15−y gives 2(15−y)+3y=36⟹y=6,x=9, point (9,6)
Feasible region vertices: (0,3),(0,12),(9,6),(12,3).
Evaluate Z=3x+5y at each:
- (0,3): Z=15
- (0,12): Z=60
- (9,6): Z=27+30=57
- (12,3): Z=36+15=51
By the corner-point theorem, the maximum and minimum of Z over the feasible region occur at vertices: maximum Z=60 at (0,12), minimum Z=15 at (0,3).
OR: Minimize Z=3x+9y subject to x+3y≤60, x+y≥10, x≤y, x≥0,y≥0.
Corner points of the feasible region:
- x+y=10 and x=y: x=y=5, point (5,5)
- x+y=10 and x=0: point (0,10)
- x+3y=60 and x=0: point (0,20)
- x+3y=60 and x=y: 4x=60⟹x=y=15, point (15,15)
Evaluate Z=3x+9y:
- (0,10): Z=90
- (5,5): Z=15+45=60
- (15,15): Z=45+135=180
- (0,20): Z=180
The minimum value is Z=60 at (5,5), which is the vertex closest to the origin-side boundary x+y=10 meeting x=y; every other feasible vertex gives a strictly larger Z, and the region between vertices along each edge varies monotonically since Z is linear, so the vertex minimum is the true minimum.
✓Final answerMain: maximum Z=60 at (0,12), minimum Z=15 at (0,3). OR: minimum Z=60 at (5,5).
- AHSEC Higher Secondary (HS) Final Examination 2024Set ANNUAL6 marksQ.Solve graphically the following linear programming problem: Maximize and minimize Z=x+2y subject to x+2y≥100, 2x−y≤0, 2x+y≤200, x,y≥0. OR A merchant plans to sell two types of personal computers—a desktop model and a portable model that will cost Rs. 25,000 and Rs. 40,000 respectively. He estimates that the total monthly demand of computers will not exceed 250 units. Determine the number of units of each type of computers which the merchant should stock to get maximum profit if he does not want to invest more than Rs. 70 lakhs and if his profit on the desktop model is Rs. 4,500 and on portable model is Rs. 5,000.
›Reveal solutionSolution
Graph the constraints, find the feasible-region corner points, and evaluate the objective at each; the OR part is a max-profit LPP solved the same way.
Main question: Constraints: x+2y≥100, 2x−y≤0 (i.e. y≥2x), 2x+y≤200, x,y≥0.
Find the corner points of the feasible region by pairwise intersection of the boundary lines (keeping only points satisfying all constraints):
- x+2y=100 meets the y-axis (x=0) at (0,50) — check: y≥2x (50≥0 ✓), 2x+y=50≤200 ✓.
- x+2y=100 meets y=2x: substituting, x+4x=100⇒x=20,y=40, point (20,40).
- y=2x meets 2x+y=200: 2x+2x=200⇒x=50,y=100, point (50,100).
- 2x+y=200 meets the y-axis at (0,200) — check: x+2y=400≥100 ✓, y≥2x (200≥0 ✓).
(The point (100,0), where x+2y=100 meets the x-axis, is rejected since it violates y≥2x.)
So the feasible region is the quadrilateral with vertices (0,50),(20,40),(50,100),(0,200).
Evaluate Z=x+2y:
Point Z=x+2y (0,50) 100 (20,40) 100 (50,100) 250 (0,200) 400 Since (0,50) and (20,40) both lie on the line x+2y=100 and give the same Z=100, the minimum Z=100 is attained at every point of the segment joining them (multiple optimal solutions). The maximum Z=400 occurs uniquely at (0,200).
OR: Let x = number of desktops, y = number of portables.
Budget: 25000x+40000y≤70,00,000⇒5x+8y≤1400 (dividing by 5000).
Demand: x+y≤250. Also x,y≥0.
Maximize profit P=4500x+5000y.
Corner points:
- (0,0)
- (250,0) (demand line meets x-axis; budget 5(250)=1250≤1400, feasible)
- Intersection of 5x+8y=1400 and x+y=250: substitute x=250−y: 5(250−y)+8y=1400⇒1250+3y=1400⇒y=50,x=200, giving (200,50)
- (0,175) (budget line meets y-axis: 8y=1400⇒y=175; demand check 175≤250 ✓)
Evaluate P=4500x+5000y:
Point Profit (0,0) 0 (250,0) 11,25,000 (200,50) 11,50,000 (0,175) 8,75,000 Maximum profit = Rs. 11,50,000, attained at (200,50) — i.e. 200 desktop models and 50 portable models.
✓Final answerMain: minimum Z=100 (segment from (0,50) to (20,40)); maximum Z=400 at (0,200). OR: stock 200 desktops and 50 portables for a maximum profit of Rs. 11,50,000.
- AHSEC Higher Secondary (HS) Final Examination 2023Set ANNUAL6 marksQ.Solve graphically the following linear programming problem. Maximize and minimize Z=−x+2y subject to the constraints x≥2, x+y≥5, x+2y≥6, y≥0. OR A manufacturer makes two types of toys A and B. Three machines are needed for this purpose and the time (in minutes) required for each toy on the machines is given below: Machine I / II / III — Toy A: 12, 18, 6; Toy B: 6, 0, 9. Each machine is available for a maximum of 6 hours per day. If the profit on each toy of type A is Rs. 7.50 and that on each toy of type B is Rs. 5, show that 15 toys of type A and 30 toys of type B should be manufactured in a day to get maximum profit.
›Reveal solutionSolution
Plot the corner points of the unbounded feasible region and test, via the half-plane method, whether Z is bounded in either direction — here it is unbounded both ways.
Constraints: x≥2, x+y≥5, x+2y≥6, y≥0. Since all inequalities are "≥" (plus y≥0), the feasible region lies above/right of these boundary lines and is unbounded.
Corner points (intersections of the boundary lines, checked for feasibility):
- x=2 and x+y=5: gives (2,3). (Check x+2y=2+6=8≥6 ✓.)
- x+y=5 and x+2y=6: subtracting gives y=1, x=4, i.e. (4,1). (Check x≥2 ✓.)
- x+2y=6 and y=0: gives (6,0). (Check x+y=6≥5 ✓, x≥2 ✓.)
The region is bounded by these three segments but extends unboundedly: upward along x=2 (for y≥3) and rightward along y=0 (for x≥6).
Evaluate Z=−x+2y at the corners:
Z(2,3)=−2+6=4,Z(4,1)=−4+2=−2,Z(6,0)=−6+0=−6.
Testing for a maximum: Consider the open half-plane −x+2y>4. The point (2,100) lies in the feasible region (satisfies x≥2, x+y=102≥5, x+2y=202≥6, y≥0) and gives Z=−2+200=198>4. Since this half-plane intersects the feasible region, Z can be made arbitrarily large along x=2 as y→∞ — so Z has no maximum value.
Testing for a minimum: Consider the open half-plane −x+2y<−6. The point (100,0) is feasible (satisfies all constraints) and gives Z=−100<−6. Since this half-plane also intersects the feasible region, Z can be made arbitrarily small (large negative) along y=0 as x→∞ — so Z has no minimum value either.
Hence, over this unbounded feasible region, Z=−x+2y is unbounded in both directions: neither a maximum nor a minimum exists.
OR: Toys A,B; machine-minute constraints (converting 6 hours =360 minutes each):
I: 12x+6y≤360⇒2x+y≤60,II: 18x≤360⇒x≤20,III: 6x+9y≤360⇒2x+3y≤120,x,y≥0.
Maximize Z=7.5x+5y.
Corner points of the feasible region: (0,0), (20,0), (20,20) [intersection of x=20 and 2x+y=60], (15,30) [intersection of 2x+y=60 and 2x+3y=120], (0,40) [intersection of 2x+3y=120 and x=0].
Z(0,0)=0,Z(20,0)=150,Z(20,20)=7.5(20)+5(20)=250,Z(15,30)=7.5(15)+5(30)=112.5+150=262.5,Z(0,40)=200.
The maximum is Z=262.5, attained at (15,30) — confirming that 15 toys of type A and 30 toys of type B give the maximum profit of Rs. 262.50 per day.
✓Final answerZ=−x+2y has neither a maximum nor a minimum (unbounded region, unbounded objective both ways). (OR) Max profit Rs. 262.50 at 15 type-A + 30 type-B toys, confirmed.
- AHSEC Higher Secondary (HS) Final Examination 2022Set ANNUAL6 marksQ.Minimize Z=3x+5y subject to x+3y≥3, x+y≥2, x,y≥0. OR Minimise and Maximise Z=5x+10y subject to x+2y≤120, x+y≥60, x−2y≥0, x,y≥0.
›Reveal solutionSolution
Evaluating Z=3x+5y at the feasible region's corner points gives the minimum 7 at (3/2,1/2). (OR: the classic two-constraint LPP has minimum 300 at (60,0) and maximum 600 along the whole edge from (120,0) to (60,30).)
Minimize Z=3x+5y subject to x+3y≥3, x+y≥2, x,y≥0
Find the corner points of the feasible region (intersection of the boundary lines with each other and the axes, keeping only feasible points):
- On y=0: need x≥3 (from x+3y≥3) and x≥2 (from x+y≥2) — the binding one is x=3, giving corner (3,0).
- On x=0: need y≥1 and y≥2 — binding is y=2, giving corner (0,2).
- Intersection of x+3y=3 and x+y=2: subtracting, 2y=1⇒y=21, then x=23 — corner (23,21).
The feasible region is unbounded, with corners (3,0), (23,21), (0,2) (and extending outward).
Evaluate Z=3x+5y:
Z(3,0)=9,Z(23,21)=29+25=7,Z(0,2)=10.
Since both coefficients of Z are positive and the region extends only outward (away from the origin), Z cannot go below the smallest corner value; the open half-plane 3x+5y<7 has no point in common with the feasible region. So the minimum is Z=7 at (23,21).
OR: Minimise and Maximise Z=5x+10y subject to x+2y≤120, x+y≥60, x−2y≥0, x,y≥0
Finding all feasible corner points (checking each pairwise intersection against all constraints):
- x+2y=120 and x=2y: y=30,x=60 — (60,30), feasible.
- x+2y=120 and y=0: (120,0), feasible.
- x+y=60 and x=2y: y=20,x=40 — (40,20), feasible.
- x+y=60 and y=0: (60,0), feasible.
(Points like (0,60) or (0,0) fail the x≥2y or x+y≥60 constraint and are not corners of the feasible region.)
Evaluate Z=5x+10y:
Z(60,0)=300,Z(120,0)=600,Z(60,30)=300+300=600,Z(40,20)=200+200=400.
Minimum Z=300 at (60,0).
Maximum Z=600, attained at both (120,0) and (60,30) — since these both lie on the line x+2y=120 and Z=5x+10y=5(x+2y) is constant (=600) all along that edge, the maximum is attained at every point of the line segment joining (120,0) and (60,30) (multiple optimal solutions).
✓Final answerMinimum Z=7 at (3/2,1/2). [OR: Minimum Z=300 at (60,0); Maximum Z=600 at every point on the segment joining (120,0) and (60,30).]
- AHSEC Higher Secondary (HS) Final Examination 2020Set ANNUAL6 marksQ.Solve graphically the following linear programming problem: Maximize or Minimize Z=x+2y subject to constraints x+2y≥100, 2x−y≤0, 2x+y≤200, x≥0, y≥0. OR Maximize Z=1000x+600y subject to constraints x+y≤200, x≥20, y≥4x, x≥0, y≥0.
›Reveal solutionSolution
Plot the feasible region from the constraints, find its corner points, then evaluate the objective function at each corner.
Max/Min Z=x+2y s.t. x+2y≥100, 2x−y≤0, 2x+y≤200, x,y≥0
Rewrite 2x−y≤0 as y≥2x.
Corner points (solving pairs of boundary lines and checking they satisfy all constraints):
- x+2y=100 and y=2x: x+4x=100⇒x=20,y=40 → (20,40)
- y=2x and 2x+y=200: 2x+2x=200⇒x=50,y=100 → (50,100)
- x=0 with x+2y=100: y=50 → (0,50) (since at x=0, need y≥50 from constraint 1)
- x=0 with 2x+y=200: y=200 → (0,200) (upper bound at x=0)
These four points (0,50),(20,40),(50,100),(0,200) form the (bounded) feasible region.
Evaluate Z=x+2y:
- (0,50): Z=100
- (20,40): Z=100
- (50,100): Z=250
- (0,200): Z=400
Minimum Z=100 (attained all along the edge joining (0,50) and (20,40), since that edge lies exactly on x+2y=100). Maximum Z=400 at (0,200).
OR: Maximize Z=1000x+600y s.t. x+y≤200, x≥20, y≥4x, x,y≥0
At x=20: y≥80 and y≤180, giving corners (20,80) and (20,180).
y=4x meets x+y=200: x+4x=200⇒x=40,y=160 → (40,160).
Feasible region is the triangle with vertices (20,80),(20,180),(40,160).
Evaluate Z=1000x+600y:
- (20,80): Z=20000+48000=68000
- (20,180): Z=20000+108000=128000
- (40,160): Z=40000+96000=136000
Maximum Z=136000 at x=40,y=160.
✓Final answerMin Z=100 (edge (0,50)–(20,40)); Max Z=400 at (0,200). (OR: Max Z=136000 at (40,160).)
- AHSEC Higher Secondary (HS) Final Examination 2019Set ANNUAL6 marksQ.Solve the linear programming problem graphically. Maximize z=20x+15y, subject to the conditions 2x+y≤200, x+y≤150 and x≥0, y≥0. OR Maximize and minimize z=5x+2y, subject to the conditions x−2y≤2, 3x+2y≤12, −3x+2y≤3 and x≥0, y≥0.
›Reveal solutionSolution
In each LPP, plot the constraint lines, find the vertices of the feasible region, and evaluate the objective at each vertex — the optimum occurs at a vertex (corner-point method).
Main question. Maximize z=20x+15y subject to 2x+y≤200, x+y≤150, x,y≥0.
Find the corner points of the feasible region.
- Intersection of 2x+y=200 and x+y=150: subtracting, x=50, so y=100. Point (50,100).
- y=0: 2x+y=200⇒x=100 (binding, since x+y≤150 allows x up to 150, so 200-line is tighter) — vertex (100,0).
- x=0: x+y=150⇒y=150 (binding, since 2x+y≤200 allows y up to 200) — vertex (0,150).
- Origin (0,0).
Evaluate z=20x+15y:
Vertex z (0,0) 0 (100,0) 2000 (50,100) 1000+1500=2500 (0,150) 2250 Maximum is z=2500 at (50,100).
OR question. Maximize and minimize z=5x+2y subject to x−2y≤2, 3x+2y≤12, −3x+2y≤3, x,y≥0.
Find the vertices.
- x=0: constraints give y≤6 (from 3x+2y≤12) and y≤1.5 (from −3x+2y≤3); tightest is y≤1.5 — vertex (0,1.5); also (0,0).
- y=0: constraints give x≤2 (from x−2y≤2) and x≤4 (from 3x+2y≤12); tightest is x≤2 — vertex (2,0).
- Intersection of x−2y=2 and 3x+2y=12: adding, 4x=14⇒x=3.5, y=2x−2=0.75. Vertex (3.5, 0.75) — check −3(3.5)+2(0.75)=−9≤3 ✓ feasible.
- Intersection of 3x+2y=12 and −3x+2y=3: adding, 4y=15⇒y=3.75, 3x=12−7.5=4.5⇒x=1.5. Vertex (1.5, 3.75) — check x−2y=1.5−7.5=−6≤2 ✓ feasible.
So the feasible region has vertices (0,0), (2,0), (3.5,0.75), (1.5,3.75), (0,1.5).
Evaluate z=5x+2y:
Vertex z (0,0) 0 (2,0) 10 (3.5,0.75) 17.5+1.5=19 (1.5,3.75) 7.5+7.5=15 (0,1.5) 3 Maximum z=19 at (3.5, 0.75)=(27,43); minimum z=0 at (0,0).
✓Final answerMain part: max z=2500 at (50,100). OR part: max z=19 at (27,43), min z=0 at (0,0).
- AHSEC Higher Secondary (HS) Final Examination 2018Set ANNUAL6 marksQ.Solve the Linear Programming Problem graphically: Maximize and Minimize z=6x+3y subject to 4x+y≥80, x+5y≥115, 3x+2y≤150, x≥0,y≥0.
›Reveal solutionSolution
The feasible region is a triangle with corners (2,72),(15,20),(40,15); evaluating z=6x+3y gives min 150 and max 285.
Maximize/minimize z=6x+3y subject to 4x+y≥80, x+5y≥115, 3x+2y≤150, x,y≥0.
Find the corner points by intersecting the boundary lines:
- 4x+y=80 and x+5y=115: solving gives (15,20).
- 4x+y=80 and 3x+2y=150: solving gives (2,72).
- x+5y=115 and 3x+2y=150: solving gives (40,15).
Each of these satisfies all constraints, so the feasible region is the triangle with vertices (2,72), (15,20), (40,15).
Evaluate z=6x+3y at each corner:
- (2,72):z=12+216=228
- (15,20):z=90+60=150
- (40,15):z=240+45=285
So the minimum is 150 at (15,20) and the maximum is 285 at (40,15).
✓Final answerMinimum z=150 at (15,20); Maximum z=285 at (40,15).
OR (alternative question): Max/min z=800x+1200y s.t. 3x+4y≤60, x+3y≤30, x,y≥0.
Corners: (0,0),(20,0),(0,10) and the intersection of 3x+4y=60, x+3y=30, which is (12,6). Values: z(0,0)=0, z(20,0)=16000, z(0,10)=12000, z(12,6)=9600+7200=16800. So minimum z=0 at (0,0) and maximum z=16800 at (12,6).
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