Simple models of irreversible dynamics on networks have been successfully applied to describe cascade processes in many fields of research. However the problem of optimizing the trajectory of the system, e.g. obtain the largest propagation using the smallest set of seeds, is still considered to be practically intractable in large networks. I will present a new formulation of the problem that exploits the cavity method to develop an efficient message passing algorithm that solves several types of spread optimization processes on very large networks. In the controlled setup provided by random graphs I will also discuss the mechanisms underlying the optimized dynamics, showing that the performances depend on the strength of the dynamical cooperative effects.