When I first delved in the world of contest math, a topic which I particularly had problems with (and still do today) was optimization. Besides memorizing various inequalities, it was also hard for me to transform such problems into a form where these inequalities can be used.
Hence I was quite anxious to solve a problem introduced to me by a friend yesterday which is as follows.
Find the maximum value of
where
What I think is peculiar with this problem is the numerator, since it seems to lack "symmetry". To explain,
My friend used the arithmetic mean - geometric mean (AM-GM) inequality to solve this problem. It involved some complicated ways of seeking the appropriate coefficients which may take too long to explain, so I will just show the core of his solution.
Let
Taking the sum of the inequalities in the right side, we obtain
Now, if we force
This upper bound is attainable for values of
As I have remarked before, the problem I have with olympiad-type optimization problems is the difficulty in manipulating the objective function into a suitable form to perform inequalities on. For instance, the solution I have shown above does not show the tedious reason why the coefficients are to be written in such a way as function of
Hence, I sought to find another way of solving the problem. One may observe that the numerator seems to appear like a dot product. Furthermore the denominator appears to be the squared Euclidean norm of the vector
Let
We can therefore view the problem as follows.
Find the maximum value of
where
This restatement seems to be more complicated than the original expression. Indeed, this is not the type of solution one may expect for an olympiad-type question. However, the advantage here is that there exists a straightforward way to solve such a problem.
In general, for an arbitrary matrix, the maximum value of the expression above does not have a general formula (at least, to my knowledge). However, our matrix
This is important because it would mean that the quantity
Therefore, the alternative solution to our problem involves finding the eigenvalues of the matrix, which is a straightforward computation.
Using the quadratic formula,
Hence, the maximum value of
While this alternative solution gives a direct way to compute for the maximum value, it is still quite complicated to do and reliant on luck. For instance, the fact that a Hermitian matrix would appear was not really predicted. Additionally, finding the zeroes of the characteristic equation may also be difficult. Nevertheless, I still find this solution using linear algebra quite useful, and I hope you, the reader, also found this interesting.
As practice for the curious reader, I will leave the following problem for you to solve. I hope you will try out the method above in solving this problem. Thanks for reading!
Find the maximum value of
where