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K-Adaptability in Two-Stage Distributionally Robust Binary Programming

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Title: K-Adaptability in Two-Stage Distributionally Robust Binary Programming
Authors: Hanasusanto, G
Kuhn, D
Wiesemann, W
Item Type: Journal Article
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 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.
Issue Date: Jul-2015
Date of Acceptance: 1-Mar-2015
URI: http://hdl.handle.net/10044/1/24503
DOI: 10.1287/opre.2015.1392
ISSN: 1526-5463
Publisher: INFORMS (Institute for Operations Research and Management Sciences)
Start Page: 877
End Page: 891
Journal / Book Title: Operations Research
Volume: 63
Issue: 4
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Funder's Grant Number: EP/I014640/1
EP/M028240/1
Keywords: Social Sciences
Science & Technology
Technology
Management
Operations Research & Management Science
Business & Economics
APPROXIMATION ALGORITHMS
STOCHASTIC PROGRAMS
INTEGER RECOURSE
DECOMPOSITION ALGORITHM
FINITE ADAPTABILITY
OPTIMIZATION
FRAMEWORK
POWER
CUT
programming
integer
stochastic
Operations Research
0102 Applied Mathematics
0802 Computation Theory and Mathematics
1503 Business and Management
Publication Status: Published
Online Publication Date: 2015-06-29
Appears in Collections:Imperial College Business School



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