Maximizing a Function with a Constraint: The Lagrangian Approach

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In summary, the conversation discusses solving a problem using Lagrangian optimization and finding the maximum of a function subject to a constraint. It is determined that the function has no global maximum, but there is a local minimum at x=y=(1/2). The possibility of a maximum at the asymptotes is also considered. There is some confusion as to why the problem was asked to be maximized if there are no maximum points, with the possibility of it being a typo.
  • #1
naturalnumbas
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Homework Statement


Seems straightforward enough, Lagrangian optimization


Homework Equations


Find the max of x^-1 + y^-1 subject to the constraint m=x+y



The Attempt at a Solution



At first I thought no problems, x*=y*=m/2, however:

Using the Lagrangian formula yields derivatives as follows:
wrt x: -x^-2 - lambda
wrt y: -y^-2 - lambda
lambda: m-x-y

Putting the coefficients into a bordered Hessian seems to give a positive def. matrix implying a minimum? Is this a trick question or is it possible to maximize?
 
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  • #2
Yes, x=y=(1/2) is a local minimum. You can also just use your constraint to eliminate y in 1/x+1/y and graph it as a function of x. As x ranges over all possible values you can see there is no global max or global min. There are vertical asymptotes.
 
  • #3
Dick said:
Yes, x=y=(1/2) is a local minimum. You can also just use your constraint to eliminate y in 1/x+1/y and graph it as a function of x. As x ranges over all possible values you can see there is no global max or global min. There are vertical asymptotes.

Thanks for the reply, you are making sense to me. I'm still confused as to why I was asked to maximize it, when there are no maximum points?
 
  • #4
naturalnumbas said:
Thanks for the reply, you are making sense to me. I'm still confused as to why I was asked to maximize it, when there are no maximum points?

Typo? Always a possibility.
 
  • #5
Dick said:
Typo? Always a possibility.

I'm thinking you are probably right.

On an exam no less :S.

Guess I should have known better. Thanks again.
 
  • #6
Although, I've been reading that extreme values can occur at endpoints, stationary points, and singular points. So obviously this function has some singular points, but I do not know enough to go any further.

Could there be a max at the asymptotes?
 
  • #7
naturalnumbas said:
Although, I've been reading that extreme values can occur at endpoints, stationary points, and singular points. So obviously this function has some singular points, but I do not know enough to go any further.

Could there be a max at the asymptotes?

As I said, graph 1/x+1/(m-x) to see what the function looks like. Yes, it's singular at x=0 and x=m. No maxes there.
 

FAQ: Maximizing a Function with a Constraint: The Lagrangian Approach

What is Lagrange again?

Lagrange is a mathematical concept named after the French-Italian mathematician Joseph-Louis Lagrange. It is used to solve optimization problems in calculus.

Why is Lagrange important?

Lagrange is important because it provides a powerful tool for solving optimization problems in various fields such as physics, economics, and engineering.

How does Lagrange work?

Lagrange works by using a set of equations called Lagrange equations to find the minimum or maximum value of a function subject to certain constraints.

What are some real-world applications of Lagrange?

Lagrange has many real-world applications, including finding the optimal path for a spacecraft to travel, minimizing energy consumption in buildings, and maximizing profits in business.

Are there any limitations to using Lagrange?

While Lagrange is a powerful tool, it does have some limitations. It can only be used for problems that can be expressed as a function with constraints. Additionally, it may not always provide the most efficient solution.

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