Solution

ID: past-exam-of-the-year-1-of-the-computer-science-course-of-the-university-of-oxford/2016/discrete-mathematics-continuous-mathematics-and-probability-resit/6/b/solution

The constraint is a compact set, so the continuous objective attains both extrema by the extreme value theorem. Use Lagrange multipliers with :
Since the second component makes , the two equations give , or . Substitution into the constraint yields
with matching signs. The objective values are therefore
The constraint gradient never vanishes on the ellipse, so these are all the possible extrema. As a direct check, set , ; then and the Cauchy-Schwarz inequality gives , with equality at the same points.

New to topics? Read the docs here!