Scenario Aggregation using Binary Decision Diagrams for Stochastic Programs with Endogenous Uncertainty
arXiv: Optimization and Control, Volume abs/1701.04055, 2017.
Modeling decision-dependent scenario probabilities in stochastic programs is difficult and typically leads to large and highly non-linear MINLPs that are very difficult to solve. In this paper, we develop a new approach to obtain a compact representation of the recourse function using a set of binary decision diagrams (BDDs) that encode a...More
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