Title	Worst-case regret minimization in a two-stage linear program
Creator	Delage, Erick
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2019-01-17T14:05
Description	In this talk, we explain how two-stage worst-case regret minimization problems can be reformulated as two-stage robust optimization models. This allows us to employ both approximate and exact solution methods that are available in the recent literature to fficiently identify good solutions for these hard problems. In particular, our numerical experiments indicate that affine decision rules are particularly effective at identifying good conservative solutions for three different types of decision problems: a multi-item newsvendor problem, a lot-sizing problem, and a production-transportation problem.
Extent	41.0
Subject	Mathematics; Operations research, mathematical programming; Computer science; Applied computer science
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: HEC Montréal
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2019-07-17
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0379887
URI	http://hdl.handle.net/2429/71024
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Researcher
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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