K-adaptability in two-stage distributionally robust binary programming

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate secondstage policies here-and-now and implement the best of these policies once the uncertain parameters have been observed. We analyze the approximation quality and the computational complexity of the K-adaptability problem, and we derive explicit mixed-integer linear programming reformulations. We also provide efficient procedures for bounding the probabilities with which each of the K second-stage policies is selected.

• Type: Journal
• Year: 2016
• Where: ORL
• Authors: Grani Adiwena Hanasusanto, Daniel Kuhn, Wolfram Wiesemann
• Keywords: Operations Research, ORL 2016