Risk-averse sequential decision problems with time-consistent stochastic dominance constraints

Darinka Dentcheva, Mingsong Ye, Yunxuan Yi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We discuss ways of comparison of two random sequences and their application in multistage stochastic optimization problems. While various comparisons of stochastic sequences have been proposed in the literature, their integration in a sequential decision problem is non-trivial and usually results in a time-inconsistent evaluations and inconsistent decisions. We propose a framework for constructing stochastic orderings that enable time-consistent comparisons at any stage of the decision process and ensure the dominance property of the optimal policy. We use the comparisons as constraints in multi-stage stochastic problems. Particular attention is paid to constraints based on stochastic dominance of the second-order imposed conditionally; it reflects risk-averse preferences and results in problems amenable to numerical treatment. We derive optimality condition for the new problems in a special case and establish relations to the expected utility theory. Additionally, we propose a numerical method for solving the new problems.

Original languageEnglish
Title of host publication2022 IEEE 61st Conference on Decision and Control, CDC 2022
Pages3605-3610
Number of pages6
ISBN (Electronic)9781665467612
DOIs
StatePublished - 2022
Event61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico
Duration: 6 Dec 20229 Dec 2022

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2022-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference61st IEEE Conference on Decision and Control, CDC 2022
Country/TerritoryMexico
CityCancun
Period6/12/229/12/22

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