# Convex optimization inside a hyper-rectangle region

I'm recently looking for algorithms for solving convex optimization problem inside a hyper-rectangle (that is, each constraint contains only one variable):

\begin{align} &\underset{\mathbf{x}}{\operatorname{minimize}}& & f(\mathbf{x}) \\ &\operatorname{subject\ to} & &a_i\leq x_i \leq b_i, \quad i = 1, \dots, m \\ \end{align}

Are there any keywords or resources about this special case of convex optimization? (hopefully for both differentiable and non-differentiable functions)