Absolutely everywhere, it is a common subproblem in many many algorithms. For example, the basin hopping algorithm (sister of SA) solves one at every step.
A specific example is in image deblurring via Tikhonov regularization, which involves minimizing a function that is provably convex for many physically realistic types of blurring.
A hill-climbing algorithm will take the lunch of every algorithm listed here if you have a clean convex optimization problem.