“…This results in a model that encodes a very large conditional scenario tree, which dramatically increases the computational complexity compared to the case with only exogenous uncertainty. Significant advances have been made in solving such stochastic programs, with approaches that focus on two general strategies: identifying redundant NACs that can be removed (Goel & Grossmann, 2006;Colvin & Maravelias, 2008;Gupta & Grossmann, 2011;Boland et al, 2016;Apap & Grossmann, 2017), and applying tailored solution algorithms based on Lagrangean decomposition (Goel & Grossmann, 2006;Gupta & Grossmann, 2014), branch-and-cut (Colvin & Maravelias, 2010), Benders decomposition (Terrazas-Moreno et al, 2012), sequential scenario decomposition (Apap & Grossmann, 2017), or heuristic knapsack decomposition (Christian & Cremaschi, 2015). Vayanos et al (2011) apply decision rules to obtain tractable conservative approximations for multistage stochastic programs with type-2 endogenous uncertain parameters that are continuously distributed.…”