Relaxations of factorable functions with convex-transformable intermediates

We propose to strengthen standard factorable relaxations of global optimization problems through the use of functional transformations of intermediate expressions. In particular, we exploit convex transformability of the component functions of factorable programs as a tool in the generation of bounds. We define suitable forms of transforming functions and assess, theoretically and computationally, the sharpness of the resulting relaxations in comparison to existing schemes.