I'm helping a student prepare for a final, and they've been provided with a set of sample problems, with approximate points that the problem would be worth. A typical long-answer, show-all-your-work problem is worth 10pts. Answer-only problems are 5pts.
The following question is given as an answer-only, 5pt question:
Minimize $f = x^4 + 2y^4 + 3z^4$ over the unit sphere.
But I cannot find an approach to solving it that seems on par with the difficulty of the problem, implied by its context.
I tried the following methods:
- I started in on this using the method of Lagrange multipliers, but the number of sub-cases is unwieldy, and would clearly take more time (not to mention writing space) than makes sense, given the context.
- I then briefly considered using Lagrange in spherical coordinates, but it is quickly apparent that this too is not a more effective method.
- I also considered taking the constraint and subbing into the original function, e.g. $x^2 = 1 - (y^2+z^2)$, which yields $$f = 1- 2(y^2 + z^2) + 2y^2z^2 + 3y^4 + 4z^4 $$ The critical point analysis is manageable, especially if one starts with this method (but I don't see how one would know this a priori).
- Finally, I tried taking a substitution $u = x^2$, $v = y^2$ and $w = z^2$, this gives the system $$\begin{cases}f = u^2 + 2v^2 + 3w^2 \\[5pt] u + v + w = 1 \end{cases}$$ which is extremely simple to solve, using Lagrange multipliers, and it gives the correct value for the minimum; however, I feel deeply uncomfortable with this substitution: I simply don't know under what conditions such a substitution is justified...
I feel like I'm circumambulating some theory that would simplify this entire question, but I can't put my finger on it.
I apologize that this isn't a more pointed question -- but I think it's a case of "Knowing the question is knowing the answer."
Any help would be greatly appreciated! Thanks in advance for your time and help!
The direct approach of $(4x^3,8y^3,12z^3)=\lambda(2x,2y,2z)$ seems straightforward.
However your method 4 is a very good one.It is often a good idea with Lagrange multipliers to choose the variables carefully.