Mathbee CBSE Mathbee · CBSE Class 12 Maths
Class 12 Linear Programming · Very Long Answer5 Marksgraphical_optimization

Class 12 Maths · Linear Programming · Very Long Answer #72

Maximize Z=7*x/10 + y subject to 2*x + 3*y ≤ 120; 2*x + y ≤ 80; -x ≤ 0; -y ≤ 0. Solve graphically.
Coordinate-derived feasible-region graph for cbse12-math-lp-p1-practice_long-023
Coordinate-derived feasible-region graph for cbse12-math-lp-p1-practice_long-023

✅ Step-by-Step Solution

Final Answer: max Z=41 at (30,20).
  1. Draw each boundary ax+by=c and retain the closed half-plane ax+by≤c; intersect all constraints, including x,y≥0.
  2. Boundary equations: 2*x + 3*y = 120; 2*x + y = 80; -x = 0; -y = 0. Use an off-line test point to choose each half-plane.
  3. Solving pairs of boundary equations and rejecting points violating any inequality gives vertices: (0,0), (0,40), (30,20), (40,0).
  4. Evaluate the objective at every vertex: (0,0) → 0; (0,40) → 40; (30,20) → 41; (40,0) → 28.
  5. The region is bounded. max Z=41 at (30,20).

📋 CBSE Stepwise Marking Scheme

  • [1 mark] Draw each boundary ax+by=c and retain the closed half-plane ax+by≤c; intersect all constraints, including x,y≥0.
  • [1 mark] Boundary equations: 2*x + 3*y = 120; 2*x + y = 80; -x = 0; -y = 0. Use an off-line test point to choose each half-plane.
  • [1 mark] Solving pairs of boundary equations and rejecting points violating any inequality gives vertices: (0,0), (0,40), (30,20), (40,0).
  • [1 mark] Evaluate the objective at every vertex: (0,0) → 0; (0,40) → 40; (30,20) → 41; (40,0) → 28.
  • [1 mark] The region is bounded. max Z=41 at (30,20).

Master Chapter 12: Linear Programming

Practise interactive questions, flashcards, visual mind maps, and timed board tests for Linear Programming.
📘 Chapter Notes & All Exercises 🚀 Open in Interactive Workspace →
← Previous Question
Maximize Z=45000*x + 5000*y subject to x + y ≤ 250; 5*x + 8*y ≤…
Next Question →
A feasible polygon has boundary vertices…

More Practice Questions in Linear Programming

Related Questions in Linear Programming