Title	Measuring the Value of Randomized Solutions in Distributionally Robust Optimization
Creator	Delage, Erick
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2018-03-09T09:47
Description	This talk studies the value of randomized solutions (VRS) in distributionally robust mixed integer programming problems. We show different methods for obtaining upper bounds on VRS and identify conditions under which some of them are tight. We also devise and implement a column-generation algorithm for identifying optimal randomized solutions in two-stage distributionally robust optimization with right-hand-side uncertainty. We empirically illustrate our findings in a capacitated facility location problem where the distribution is known to be part of a Wasserstein ambiguity set. This is joint work with Ahmed Saif.
Extent	27 minutes
Subject	Mathematics; Operations research, mathematical programming; Probability theory and stochastic processes; Operation research
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: HEC Montréal
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2018-09-06
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0371935
URI	http://hdl.handle.net/2429/67120
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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