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K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Grani A. Hanasusanto (grani.hanasusanto***at***epfl.ch)
Daniel Kuhn (daniel.kuhn***at***epfl.ch)
Wolfram Wiesemann (ww***at***imperial.ac.uk)

Abstract: We 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.

Keywords: distributionally robust optimization; integer programming; two-stage problems

Category 1: Robust Optimization

Category 2: Integer Programming

Citation:

Download: [PDF]

Entry Submitted: 04/24/2015
Entry Accepted: 04/24/2015
Entry Last Modified: 10/26/2015

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