Hanasusanto, Grani AdiwenaKuhn, DanielWiesemann, Wolfram2015-04-242015-04-242015-04-24201610.1016/j.orl.2015.10.006https://infoscience.epfl.ch/handle/20.500.14299/113525WOS:000370105400002We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate second-stage 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.Distributionally robust optimizationInteger programmingtwo-stage problemstext::journal::journal article::research article