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Scenario decomposition of risk-averse stochastic optimization problems

Descriptive

TypeOfResource
Text
TitleInfo (ID = T-1)
Title
Scenario decomposition of risk-averse stochastic optimization problems
Identifier
ETD_2836
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000056283
Language
LanguageTerm (authority = ISO639-2); (type = code)
eng
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Operations Research
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Stochastic programming
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Decomposition (Mathematics)
Subject (ID = SBJ-4); (authority = ETD-LCSH)
Topic
Risk-return relationships
Abstract (type = abstract)
In the last decade the theory of coherent risk measures established itself as an alternative to expected utility models of risk averse preferences in stochastic optimization. Recently, increased attention is paid to dynamic measures of risk, which allow for risk-averse evaluation of streams of costs or rewards. When used in stochastic optimization models, dynamic risk measures lead to a new class of problems, which are significantly more complex than their risk-neutral counterparts. Decomposition, an established and efficient approach to risk-neutral multistage stochastic optimization problems, cannot be directly applied to risk-averse models. With dynamic risk measures, the main feature facilitating decomposition, the integral form of the objective function, is absent. Our main objective is to overcome this difficulty by exploiting specific structure of dynamic risk measures, and to develop new decomposition methods that extend the ideas of earlier approaches to risk-neutral problems. In this work we develop generalizations of scenario decomposition methods, in the spirit of J.M. Mulvey and A. Ruszczynski, "A new scenario decomposition method for large-scale stochastic optimization'" Operations Research 43, 1995. The key to success is the use of dual properties of dynamic measures of risk to construct a family of risk-neutral approximations of the problem. First, we define and analyze a two-stage risk-averse stochastic optimization problem. Next, we develop methods to solve efficiently this problem. Later, we formally define a multistage risk-averse stochastic optimization problem and we discuss its properties. We also develop efficient methods to solve the multistage problem and apply these to an inventory planning and assembly problem. Finally, we analyze and compare the results of our computational experiments.
PhysicalDescription
Form (authority = gmd)
electronic resource
Extent
vi, 85 p.
InternetMediaType
application/pdf
InternetMediaType
text/xml
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
Note (type = statement of responsibility)
by Ricardo A. Collado Soto
Name (ID = NAME-1); (type = personal)
NamePart (type = family)
Collado
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Ricardo
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1975-
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author
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Ricardo Collado
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Avi-Ithzak
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Benjamin
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chair
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Advisory Committee
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Benjamin Avi-Ithzak
Name (ID = NAME-3); (type = personal)
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Ruszczynski
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Andrzej
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co-chair
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Advisory Committee
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Andrzej Ruszczynski
Name (ID = NAME-4); (type = personal)
NamePart (type = family)
Boros
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Endre
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internal member
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Advisory Committee
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Endre Boros
Name (ID = NAME-5); (type = personal)
NamePart (type = family)
Jeong
NamePart (type = given)
Myong
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internal member
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Advisory Committee
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Myong Jeong
Name (ID = NAME-6); (type = personal)
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Dentcheva
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Darinka
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outside member
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Advisory Committee
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Darinka Dentcheva
Name (ID = NAME-7); (type = personal)
NamePart (type = family)
Alizadeh
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Farid
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outside member
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Advisory Committee
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Farid Alizadeh
Name (ID = NAME-8); (type = personal)
NamePart (type = family)
Eckstein
NamePart (type = given)
Jonathan
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outside member
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Advisory Committee
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Jonathan Eckstein
Name (ID = NAME-9); (type = personal)
NamePart (type = family)
Bayal-Gursoy
NamePart (type = given)
Melike
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outside member
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Advisory Committee
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Melike Bayal-Gursoy
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
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degree grantor
Name (ID = NAME-2); (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
OriginInfo
DateCreated (qualifier = exact)
2010
DateOther (qualifier = exact); (type = degree)
2010-10
Place
PlaceTerm (type = code)
xx
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3H131TD
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (AUTHORITY = GS); (ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder (ID = PRH-1); (type = personal)
Name
FamilyName
Collado
GivenName
Ricardo
Role
Copyright Holder
RightsEvent (ID = RE-1); (AUTHORITY = rulib)
Type
Permission or license
DateTime
2010-09-01 11:40:44
AssociatedEntity (ID = AE-1); (AUTHORITY = rulib)
Role
Copyright holder
Name
Ricardo Collado
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject (ID = AO-1); (AUTHORITY = rulib)
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.
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Technical

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ETD
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application/pdf
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application/x-tar
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