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Time-consistent approximations of risk-averse multistage stochastic optimization problems
Descriptive
TitleInfo
Title
Time-consistent approximations of risk-averse multistage stochastic optimization problems
Name
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Asamov
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Tsvetan
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1985-
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Tsvetan Asamov
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author
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Ruszczynski
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Andrzej
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Andrzej Ruszczynski
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Advisory Committee
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chair
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BEN-ISRAEL
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ADI BEN-ISRAEL
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Advisory Committee
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internal member
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Elsayed A.
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Elsayed A. Elsayed
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Advisory Committee
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internal member
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Roberts
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Fred
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Fred Roberts
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Advisory Committee
Role
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internal member
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Dentcheva
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Darinka
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Darinka Dentcheva
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Advisory Committee
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outside member
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Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
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Text
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theses
OriginInfo
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2013
DateOther
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(type = degree)
2013-10
Place
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xx
Language
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(type = code)
eng
Abstract
(type = abstract)
In this work we study the concept of time consistency as it relates to multistage risk-averse stochastic optimization problems on finite scenario trees. We use dynamic time-consistent formulations to approximate problems having a single global coherent risk measure applied to the aggregated costs over all time periods. The duality of coherent risk measures is employed to create a time-consistent cutting plane algorithm for the construction of non-parametric time-consistent approximations where every one- step conditional risk measure is specified only by its dual representation. Moreover, we show that the method can be extended to generate parametric approximations involving compositions of risk measures from a specified family. Additionally, we also consider the case when the objective function is the mean-upper semideviation measure of risk and develop methods for the construction of universal time-consistent upper bounding functions. We prove that such functions provide time-consistent upper bounds to the global risk measure for an arbitrary feasible policy. Finally, the quality of the approximations generated by the proposed methods is analyzed in multiple computational experiments involving two-stage scenario trees with both artificial data, as well as stock return data for the components of the Dow Jones Industrial Average stock market index. Our numerical results indicate that the dynamic time-consistent formulations closely approximate the original problem for a wide range of risk aversion parameters.
Subject
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Topic
Operations Research
RelatedItem
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Title
Rutgers University Electronic Theses and Dissertations
Identifier
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Identifier
ETD_4944
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
x, 91 p. : ill.
Note
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Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Tsvetan Asamov
Subject
(authority = ETD-LCSH)
Topic
Stochastic processes
Subject
(authority = ETD-LCSH)
Topic
Operations research
Subject
(authority = ETD-LCSH)
Topic
Time management
RelatedItem
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3M906P7
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Asamov
GivenName
Tsvetan
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2013-08-21 13:04:21
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Name
Tsvetan Asamov
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
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License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime
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2013-10-31
DateTime
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2014-10-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2014.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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windows xp
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Statistical Profile