“…A variety of optimization techniques have been proposed to solve these problems. Examples for the deterministic case are mathematical programming [52,59], neural networks [31], Lagrangian relaxation [24,30,33,37] and metaheuristics, in particular genetic algorithms [20,40]. When stochastic issues are considered, two main optimization techniques are 3 reported, namely, stochastic programming [12] and stochastic dynamic programming [8,22,48].…”