Maximization algorithm for the product function in R^2

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Is there any smart way to maximize the function $f:\mathbb{R}^2_{++} \to \mathbb{R} $, $(x,y)\mapsto xy$ constrained to a given convex subset of $\mathbb{R}^2_{++}$ ?

Does exist some remarkable cases in which there are smart solutions to this problem?

(note: $\mathbb{R}^2_{++}:=\{(x,y)\in \mathbb{R}^2: x\geq 0 \land y \geq 0 \} $)