Title	Discrete Convexity and Dynamic Robust Optimization
Creator	Iancu, Dan
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2018-03-06T17:36
Description	We discuss necessary and sufficient conditions for the optimality of specific classes of policies in dynamic robust optimization. We then focus on the specific case of affine policies, and show how our conditions can be used to recover and generalize several existing results in the literature. Our treatment draws interesting connections with the theory of discrete convexity (L-natural / M-natural convexity and multimodularity) and global concave envelopes, which may be of independent interest. Time permitting, we also discuss some related applications of the results in the context of a learning and stopping problem. This is joint work with Yehua Wei.
Extent	35 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: Stanford University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2018-09-03
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0371894
URI	http://hdl.handle.net/2429/67078
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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Discrete Convexity and Dynamic Robust Optimization Iancu, Dan

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