Backward Stochastic Differential Equations (BSDEs) have been successfully applied to represent the value of optimal control problems for controlled
stochastic differential equations. Since in the classical framework several restrictions on the scope of applicability of this method remained, in recent times several approaches have been devised to obtain the desired probabilistic representation in more general situations. We will review the so called randomization method, originally introduced by B. Bouchard in the framework of optimal switching problems, which consists in introducing an auxiliary,`randomized'' problem with the same value as the original one, where the control process is replaced by an exogenous random point process,and optimization is performed over a family of equivalent probability measures. The value of the randomized problem is then represented
by means of a special class of BSDEs with a constraint on one of the unknown processes.This methodology will be applied in the framework of controlled evolution equations (with immediate applications to controlled SPDEs), a case for which very few results are known so far.