The complexity of reality can be better represented by models able to involve uncertainty and time patterns. We present a general formulation of a stochastic dynamic multiobjective optimization model and we provide different solution concepts based on its transformation into different deterministic equivalent models. We provide two applications to sustainable decision making in portfolio management and optimal workforce allocation.
