Sigma Percentile
JEE Main 2021 (17 March Shift 1)
LEVELJEE Advanced

Animated Solution for Mathematics - Differentiation: The maximum value of in the following equation , where and for and is ____ (Round off to the Nearest Integer)

Enter Numerical Value:

Visualized Solution

Defining the Objective Function

  • Objective Function:
  • We can rewrite this as:
  • Goal: Find the maximum value of subject to given constraints.

Identifying the Constraints

  • Constraint 1:
  • Constraint 2:
  • Non-negativity:

Visualizing the Feasible Region

  • Line 1 Intercepts: and
  • Line 2 Intercepts: and
  • The feasible region is bounded by .
  • Constraint 2 is the active boundary.

Expressing in terms of

  • From , we get:

Substituting into the Objective Function

  • Substitute into :

Simplifying the Expression for

  • Simplify the expression:

Applying the Derivative Test

  • Let
  • Differentiate with respect to :
  • Set for maximum.

Solving for

  • Solve for :

Calculating the corresponding

  • Substitute into :

Verifying the First Constraint

  • Check :
  • (Condition Satisfied)

Calculating the Maximum Value

  • Substitute into :

Final Computation and Rounding

  • Rounding to the nearest integer:
  • Final Answer: 904

The Sigma Insight: Maxima and Minima

Solution Diagram

The Art of Optimization

Finding the Peak
Welcome, fellow traveler on the path to JEE mastery! Today, we are not just solving an equation; we are embarking on a journey of optimization.
We are given an objective function, , and we want to find its absolute maximum value. We are bound by the constraints and , with the added condition that .
This is the classic setup of a constrained optimization problem, and it is a beautiful dance between algebra and geometry.

Phase 1

The Landscape of Constraints
Imagine you are standing in the first quadrant of the Cartesian plane. You have two fences, and . These fences define your 'feasible region'—the only place where you are allowed to exist.
If you plot these lines, you will notice something fascinating. Both lines intersect the -axis at . However, the second line, , has a smaller -intercept than the first.
This means the second line is 'tighter' and encloses a smaller area. Any point that satisfies will automatically satisfy . Thus, the first constraint is redundant, and we can focus entirely on the boundary .

Phase 2

The Reduction
We have a function and a constraint . We want to maximize . Since increases as and increase, we know the maximum must lie on the boundary.
Let's reduce this two-variable problem to a single-variable one. From our active constraint, we can isolate :
This is our key. By substituting this into our objective function, we transform the problem into a simple quadratic function of .

Phase 3

The Calculus of Peaks
Let's perform the substitution: . Substituting , we get:
Simplifying this, we obtain:
Now, we have a function . This is a downward-opening parabola. To find its peak, we take the derivative with respect to and set it to zero:
Solving this gives . This is the -coordinate of our maximum.

Phase 4

The Grand Finale
With , we find the corresponding using , which yields:
We verify this point against our constraints, and it fits perfectly. Finally, we calculate the maximum value:
Rounding to the nearest integer, we arrive at 904. You have successfully navigated the constraints and found the peak! Remember, in JEE, it is not just about the calculation; it is about understanding the geometry behind the algebra.

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