Maximizing u(x, y) with A and B constraints: Tips from Gekkoo

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In summary, the conversation discusses the need for help in maximizing a function with a constraint. The method of Lagrange multipliers is suggested as a possible solution, and an alternative method is also proposed. Steps for solving the problem using the alternative method are outlined.
  • #1
Gekkoo
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Homework Statement



I need help to maximize the below function:

Homework Equations



Maximize u(x, y) = x^α * y^β subject to Ax + By = m

Any help is greatly appreciated!

/ Gekkoo
 
Last edited:
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  • #3
I'm a big fan of "Lagrange Multipliers" but if you don't know that method, you could just write y= (m- Ax)/B so that [itex]x^\alpha*y^\beta= x^\alpha*(m-Ax)^\beta/B^\beta[/itex]. Now, do you know how to find maxima and minima for that?
 
  • #4
Thanks for your answers.

1 Solve constraint for y:

y=(m-Ax)/B

2 Plug into objective function:

u=x^α*[(m-Ax)/B]^β

3 Diff w.r.t. x & equate to zero to get critical point:

FOC: x^α*ln(x)*?=0

4 Solve FOC for x:

x=?

5 Plug that into constraint to get value for y:

y = (m-A[?])/B

6 Than I have a candidate solution & need to check SOC of objective function w.r.t x!

But I fail to successfully derive FOC. Can anyone please help me out?
 

1. How can I maximize the function?

To maximize a function, you need to take the derivative of the function and set it equal to zero. Then, solve for the variable to find the critical points. Plug these critical points into the second derivative to determine whether it is a maximum or a minimum. The point with the highest value is the maximum of the function.

2. What are some strategies for maximizing a function?

Some common strategies for maximizing a function include taking the derivative, setting it equal to zero, and solving for the variable. You can also use the first and second derivative tests to determine the nature of the critical points. Additionally, you can use optimization techniques such as the gradient descent method to find the maximum value of a function.

3. What are some common mistakes when trying to maximize a function?

One common mistake is not considering all possible critical points when setting the derivative equal to zero. It's important to check the second derivative at each critical point to determine the nature of the extremum. Another mistake is not checking the endpoints of the function's domain, which can also be potential maximum points.

4. How can I use technology to help maximize a function?

There are many tools available to help with maximizing functions, such as graphing calculators and computer programs like MATLAB or Wolfram Alpha. These tools can quickly and accurately calculate derivatives and critical points, making it easier to find the maximum value of a function.

5. Can I apply the same techniques to maximize any type of function?

The techniques for maximizing a function can vary depending on the type of function. For example, maximizing a linear function is straightforward, while maximizing a quadratic function requires finding the vertex. Higher-order functions may require more advanced techniques, such as the chain rule or integration. It's important to understand the properties of the specific function you are trying to maximize in order to choose the appropriate technique.

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