Functional optimization problem

In summary, the problem is to maximize the functional \int_{-1}^1 x^3 g(x) where g is subject to certain conditions, including \int^1_{-1} |g(x)|^2 dx = 1. It is a calculus of variations problem which can be solved using the Euler-Lagrange equation with Lagrange multipliers. The solution involves finding a function g that satisfies the conditions and maximizes the given integral.
  • #1
phreak
134
1

Homework Statement



Maximize the functional [tex]\int_{-1}^1 x^3 g(x)[/tex], where g is subject to the following conditions:

[tex]\int^1_{-1} g(x)dx = \int^1_{-1} x g(x)dx = \int^1_{-1} x^2 g(x)dx = 0[/tex] and [tex]\int^1_{-1} |g(x)|^2 dx = 1[/tex].

Homework Equations



In the previous part of the problem, I computed [tex]\min_{a,b,c} \int^1_{-1} |x^3 - a - bx - cx^2|^2 dx[/tex]. I'm not sure how this is related, or if it is at all.

The Attempt at a Solution



Thus far, I have only tried to look for patterns. In particular, I've tried simply looking for functions g satisfying the conditions, without trying to maximize. I've found a few, and they seem to be closely related to the exponential function. I will continue to look, but I think I may need a boost to get started. I'll be very grateful for any hints anyone can give me.

EDIT: Hours of trying to solve this, then finally posting it to PF, then trying the Cauchy-Schwartz inequality with a bit of tricky algebra and finding the solution is really frustrating.
 
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  • #2
hi phreak, so i think this is a calculus of variations problem, have you tried using the Euler Lagrange equation with Lagrange multipliers?
 
  • #3
to expand on that, when you have the problem of optimising an integral for an unknown function g, where the integrand is given by f
[tex] \int dx f(g, g', x) [/tex]

subject to constraints h_i
[tex] \int dx h_i(g, g', x) = c_i[/tex]

then write the total equation as
[tex] L(g, g', x) = f(g, g', x) + \lambda_i h_i(g, g', x)[/tex]
where the lambda's are as yet undetermined lagrange multipliers

then the the optimising function must satisfy the Euler-Lagrange equation
[tex] \frac{\partial L(g, g', x)}{\partial g} - \frac{d}{dx} \frac{\partial L(g, g', x)}{\partial g'} = 0[/tex]
 
  • #4
note in your case a lot of thing simplify as there is no g' term in your equations
 

FAQ: Functional optimization problem

What is a functional optimization problem?

A functional optimization problem is a mathematical problem that involves finding the maximum or minimum value of a specific function. It is typically used to optimize a system or process by finding the best possible solution that satisfies a set of constraints.

What are some examples of functional optimization problems?

Some common examples of functional optimization problems include maximizing profit in a business, minimizing energy consumption in a manufacturing process, and finding the shortest route for a delivery driver.

How is a functional optimization problem solved?

Functional optimization problems are typically solved using mathematical methods such as calculus, linear programming, or dynamic programming. These methods involve finding the derivative of the function and setting it equal to zero to find the optimal solution.

What are the main challenges in solving a functional optimization problem?

The main challenges in solving a functional optimization problem include dealing with complex and non-linear functions, determining the appropriate constraints, and selecting the most efficient method for finding the optimal solution.

Can functional optimization problems be applied in real-world scenarios?

Yes, functional optimization problems are commonly used in various fields such as engineering, economics, and computer science to solve real-world problems and improve systems. They can help in decision making and finding the most efficient and effective solutions.

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