Math Problem Statement

L= 0.8logX+0.2logY+λ(5000-4x-2Y)

Solution

You have presented the following expression:

L=0.8logX+0.2logY+λ(50004X2Y)L = 0.8 \log X + 0.2 \log Y + \lambda (5000 - 4X - 2Y)

This appears to be part of an optimization problem where λ\lambda represents a Lagrange multiplier, and XX and YY are variables involved in the constraint function 50004X2Y=05000 - 4X - 2Y = 0.

To find the optimal values of XX and YY, we can follow these steps:

  1. Set up the Lagrange function: L(X,Y,λ)=0.8logX+0.2logY+λ(50004X2Y)\mathcal{L}(X, Y, \lambda) = 0.8 \log X + 0.2 \log Y + \lambda (5000 - 4X - 2Y)

  2. Take the partial derivatives of L\mathcal{L} with respect to XX, YY, and λ\lambda, and set them equal to zero:

    • Partial derivative with respect to XX: LX=0.8X4λ=0\frac{\partial \mathcal{L}}{\partial X} = \frac{0.8}{X} - 4\lambda = 0

    • Partial derivative with respect to YY: LY=0.2Y2λ=0\frac{\partial \mathcal{L}}{\partial Y} = \frac{0.2}{Y} - 2\lambda = 0

    • Partial derivative with respect to λ\lambda (this gives the constraint): Lλ=50004X2Y=0\frac{\partial \mathcal{L}}{\partial \lambda} = 5000 - 4X - 2Y = 0

  3. Solve the system of equations:

    From the first equation: 0.8X=4λλ=0.84X\frac{0.8}{X} = 4\lambda \quad \Rightarrow \quad \lambda = \frac{0.8}{4X}

    From the second equation: 0.2Y=2λλ=0.22Y=0.1Y\frac{0.2}{Y} = 2\lambda \quad \Rightarrow \quad \lambda = \frac{0.2}{2Y} = \frac{0.1}{Y}

    Now, set the expressions for λ\lambda equal to each other: 0.84X=0.1Y0.2X=0.1Y\frac{0.8}{4X} = \frac{0.1}{Y} \quad \Rightarrow \quad \frac{0.2}{X} = \frac{0.1}{Y}

    This simplifies to: 2Y=XX=2Y2Y = X \quad \Rightarrow \quad X = 2Y

  4. Substitute into the constraint: From the constraint 50004X2Y=05000 - 4X - 2Y = 0, substitute X=2YX = 2Y: 50004(2Y)2Y=050008Y2Y=05000 - 4(2Y) - 2Y = 0 \quad \Rightarrow \quad 5000 - 8Y - 2Y = 0 5000=10YY=5005000 = 10Y \quad \Rightarrow \quad Y = 500 Substituting Y=500Y = 500 into X=2YX = 2Y: X=2(500)=1000X = 2(500) = 1000

Thus, the optimal values are X=1000X = 1000 and Y=500Y = 500.

Would you like more details or have any questions? Here are some related problems:

  1. How would the results change if the coefficients in the constraint were different?
  2. What is the role of the Lagrange multiplier in this optimization?
  3. How would this problem look in a different logarithmic base, such as natural logarithms?
  4. Could this system be solved graphically? What insights could that provide?
  5. What would happen if XX and YY had boundary conditions, like non-negativity constraints?

Tip: Always ensure that the values of variables XX and YY satisfy the constraint function after solving the system.

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Math Problem Analysis

Mathematical Concepts

Optimization
Logarithms
Lagrange Multipliers
Partial Derivatives

Formulas

L = 0.8logX + 0.2logY + λ(5000 - 4X - 2Y)
Partial derivative with respect to X: ∂L/∂X = 0.8/X - 4λ = 0
Partial derivative with respect to Y: ∂L/∂Y = 0.2/Y - 2λ = 0
Partial derivative with respect to λ: ∂L/∂λ = 5000 - 4X - 2Y = 0
λ = 0.8/4X and λ = 0.1/Y

Theorems

Lagrange Multiplier Method

Suitable Grade Level

Undergraduate Level