Question 3 of 5 · Linear Programming
Questionmedium

The corner points of the feasible region of an LPP are (0, 2), (3, 0), (6, 0), (6, 8) and (0, 5). If , the minimum value of occurs at

Answer View answer ▾

Answer: Option C — every point of the segment joining (0, 2) and (3, 0)

Detailed Solution

1

at the corners: (0, 2) → 12, (3, 0) → 12, (6, 0) → 24, (6, 8) → 72, (0, 5) → 30.

2

The minimum 12 occurs at two adjacent corners, so it occurs at every point of the segment joining them.

✓ Check

The midpoint (1.5, 1) gives .

⚠ Common trap

(D) (0, 0) — (0, 0) is not a corner point of this feasible region.

Quick tip

If two adjacent corners give the same optimum, every point between them is optimal

💬 Discussions on this question

Ask a doubt ›

Still stuck on this question? Ask our faculty and fellow students — answers appear here.

Ask a doubt

More Linear Programming Questions

View all ›
  1. Q1.The maximum value of subject to , , , is
  2. Q2.The minimum value of subject to , , , is
  3. Q3.The maximum value of subject to , , , is
  4. Q4.How many corner points does the feasible region of , , , , have?

More Quantitative Aptitude Questions

  1. Q1.By selling 45 lemons for ₹40, a man loses 20%. How many lemons should he sell for ₹24 to gain 20%?Profit, Loss & Discount
  2. Q2.The marked price of an article is 1.45 times its cost price. Its selling price is ₹1,500 and the profit is 25%. What is the discount percentage? Profit, Loss & Discount
  3. Q3.Let A be a real number. Then the roots of the equation are real and distinct if and only if Quadratic Equations
  4. Q4.The number of distinct real roots of the equation is Quadratic Equations
  5. Q5.The roots of are:Quadratic Equations

Linear Programming — Preparation

This question tests your understanding of Linear Programming, a key topic in the Quantitative Aptitude section. The detailed solution above uses a step-by-step approach to show the reasoning, and where available, a shortcut that helps you solve similar questions in under 90 seconds during the actual exam.

Linear programming (LPP) is a method for finding the best outcome, such as maximum profit or minimum cost, subject to a set of linear constraints. A linear programming problem has an objective function to maximise or minimise, decision variables, and constraints written as linear inequalities, along with the condition that the variables are non-negative. In MHT CET, problems are solved graphically. Draw each constraint as a line, shade the region that satisfies all the inequalities (the feasible region), and find its corner points. The optimal value of the objective function always occurs at one of these corner points, so evaluate the objective function at each one and choose the largest or smallest value. Questions also ask you to form the LPP from a word problem, identify the feasible region from a graph, or recognise when a problem has no feasible solution or an unbounded one. Practise the linear programming questions below, each with a step-by-step graphical solution.