000207590 001__ 207590
000207590 005__ 20190317000146.0
000207590 0247_ $$2doi$$a10.1016/j.orl.2015.10.006
000207590 022__ $$a0167-6377
000207590 02470 $$2ISI$$a000370105400002
000207590 037__ $$aARTICLE
000207590 245__ $$aK-Adaptability in Two-Stage Distributionally Robust Binary Programming
000207590 260__ $$bElsevier Science Bv$$c2016$$aAmsterdam
000207590 269__ $$a2016
000207590 300__ $$a6
000207590 336__ $$aJournal Articles
000207590 500__ $$aAvailable from Optimization Online
000207590 520__ $$aWe propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate second-stage policies here-and-now and implement the best of these policies once the uncertain parameters have been observed. We analyze the approximation quality and the computational complexity of the K-adaptability problem, and we derive explicit mixed-integer linear programming reformulations. We also provide efficient procedures for bounding the probabilities with which each of the K second-stage policies is selected.
000207590 6531_ $$aDistributionally robust optimization
000207590 6531_ $$aInteger programming
000207590 6531_ $$atwo-stage problems
000207590 700__ $$0249201$$g258502$$aHanasusanto, Grani Adiwena
000207590 700__ $$g239987$$aKuhn, Daniel$$0247589
000207590 700__ $$aWiesemann, Wolfram
000207590 773__ $$j44$$tOperations Research Letters$$k1$$q6-11
000207590 8564_ $$uhttp://www.optimization-online.org/DB_HTML/2015/04/4878.html$$zURL
000207590 909C0 $$xU12788$$0252496$$pRAO
000207590 909CO $$qGLOBAL_SET$$pCDM$$ooai:infoscience.tind.io:207590$$particle
000207590 917Z8 $$x239987
000207590 917Z8 $$x239987
000207590 917Z8 $$x239987
000207590 917Z8 $$x239987
000207590 937__ $$aEPFL-ARTICLE-207590
000207590 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000207590 980__ $$aARTICLE