f(x,y) = x² + y², (x – 1)² + 4y² = 4 %3D

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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**Problem Statement:**

5) Use the method of Lagrange multipliers to find the maximum and minimum values of the function subject to the given constraints.

Function: \( f(x, y) = x^2 + y^2 \)

Constraint: \( (x - 1)^2 + 4y^2 = 4 \)

**Explanation:**

To solve this problem using the method of Lagrange multipliers, we aim to find the points where the gradient of the function \( f(x, y) \) is parallel to the gradient of the constraint. The method involves setting the gradient of the objective function equal to a multiple (λ, the Lagrange multiplier) of the gradient of the constraint.

**Steps:**

1. Define the Lagrangian: \( \mathcal{L}(x, y, \lambda) = f(x, y) - \lambda ((x-1)^2 + 4y^2 - 4) \).

2. Compute the partial derivatives of \( \mathcal{L} \) with respect to \( x, y, \) and \( \lambda \).

3. Set each of these partial derivatives to zero to find a system of equations.

4. Solve this system for \( x, y, \) and \( \lambda \).

5. Identify the points that satisfy both the original function and the constraint.

6. Determine the maximum and minimum values by evaluating \( f(x, y) \) at these points.
Transcribed Image Text:**Problem Statement:** 5) Use the method of Lagrange multipliers to find the maximum and minimum values of the function subject to the given constraints. Function: \( f(x, y) = x^2 + y^2 \) Constraint: \( (x - 1)^2 + 4y^2 = 4 \) **Explanation:** To solve this problem using the method of Lagrange multipliers, we aim to find the points where the gradient of the function \( f(x, y) \) is parallel to the gradient of the constraint. The method involves setting the gradient of the objective function equal to a multiple (λ, the Lagrange multiplier) of the gradient of the constraint. **Steps:** 1. Define the Lagrangian: \( \mathcal{L}(x, y, \lambda) = f(x, y) - \lambda ((x-1)^2 + 4y^2 - 4) \). 2. Compute the partial derivatives of \( \mathcal{L} \) with respect to \( x, y, \) and \( \lambda \). 3. Set each of these partial derivatives to zero to find a system of equations. 4. Solve this system for \( x, y, \) and \( \lambda \). 5. Identify the points that satisfy both the original function and the constraint. 6. Determine the maximum and minimum values by evaluating \( f(x, y) \) at these points.
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