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Risk-averse control of undiscounted transient Markov models
Descriptive
TitleInfo
Title
Risk-averse control of undiscounted transient Markov models
Name
(type = personal)
NamePart
(type = family)
Cavus
NamePart
(type = given)
Ozlem
NamePart
(type = date)
1981-
DisplayForm
Ozlem Cavus
Role
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(authority = RULIB)
author
Name
(type = personal)
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(type = family)
BEN-ISRAEL
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ADI
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ADI BEN-ISRAEL
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Advisory Committee
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chair
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Ruszczynski
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Andrzej
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Andrzej Ruszczynski
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Boros
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(type = given)
Endre
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Endre Boros
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Alizadeh
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(type = given)
Farid
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Farid Alizadeh
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Katehakis
NamePart
(type = given)
Michael N.
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Michael N. Katehakis
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
(type = personal)
NamePart
(type = family)
Dentcheva
NamePart
(type = given)
Darinka
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Darinka Dentcheva
Affiliation
Advisory Committee
Role
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(authority = RULIB)
outside member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
TypeOfResource
Text
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theses
OriginInfo
DateCreated
(qualifier = exact)
2012
DateOther
(qualifier = exact);
(type = degree)
2012-10
CopyrightDate
(qualifier = exact)
2012
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
The classical optimal control problems for discrete-time, transient Markov processes are infinite horizon, undiscounted expected total cost or reward models. Some examples of these models are optimal stopping problems and stochastic shortest or longest path problems, which may have applications in health-care, finance, and maintenance. However, such expected value models implicitly assume the decision maker is risk-neutral, so they may not be appropriate for several real-life problems. In this study, we use Markov risk measures to formulate a risk-averse version of the optimal control problem for transient Markov processes with general state and compact control spaces. We derive risk-averse dynamic programming equations and show that they have a unique solution which is also the optimal value of the Markov control problem. Furthermore, it is shown that a randomized policy may be strictly better than deterministic policies, when risk measures are employed. We suggest two algorithms, value iteration and policy iteration methods, for solving the dynamic programming equations and show their convergence. In general, each policy evaluation step of the policy iteration algorithm requires solving a system of nonsmooth equations. We use a version of nonsmooth Newton method to solve these equations and show its global convergence. We further consider a risk-averse finite horizon Markov control problem under randomized policies and derive a value iteration method for its solution. Finally, we work on asset selling, organ transplant, and credit card examples to illustrate the theory for infinite horizon problem, and present numerical results.
Subject
(authority = RUETD)
Topic
Operations Research
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_4195
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
ix, 79 p. : ill.
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Ozlem Cavus
Subject
(authority = ETD-LCSH)
Topic
Markov processes
Subject
(authority = ETD-LCSH)
Topic
Risk assessment
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066646
RelatedItem
(type = host)
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/T3MC8XTF
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Cavus
GivenName
Ozlem
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2012-08-19 14:20:13
AssociatedEntity
Name
Ozlem Cavus
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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