I am preparing for a talk on "Approximation Algorithms", aimed at undergraduate students. In order to motivate the topic, I want to give them an example of a problem which is easy to describe and has a ridiculously easy approximation algorithm. But the question - "Whether one can one can do better?" must be still open for that problem.
In short, what is a simple-to-describe problem whose approximation ratio is still open?
EDIT: Finding minimum Vertex Cover of a simple graph $G(V,E)$ happens to have a simple algorithm with approximation ratio 2. But its approximation ratio is still an open question.
I'd recommend approximation of functions by polynomials. Motivation is easy -- this is how computer libraries calculate trigonometric (and other) functions. Or, they used to, at least. Explanations are easy because you can draw graphs of approximations and error functions.
The obvious algorithm is Taylor expansion. This is very good near one single point and bad elsewhere, so it's fairly useless. Plot the error function.
Then try interpolation, to try to get the error function to be more "flat". How should the interpolation points be distributed? Talk about the Runge phenomenon.
End up with Chebyshev approximations and Remez algorithm. If you have access to Matlab, get the Chebfun package to play with.
For a related problem that is open (as far as I know), use approximation of 2D curves by polynomials. See this question and this one.
The second question has a good answer for circles, but it doesn't look like it generalises easily to other planar curves.