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Essays on supply chain and healthcare analytics

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TitleInfo
Title
Essays on supply chain and healthcare analytics
Name (type = personal)
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Wang
NamePart (type = given)
Yijun
NamePart (type = date)
1986-
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Yijun Wang
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author
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Zhao
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Yao
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Yao Zhao
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Advisory Committee
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chair
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Lei
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Lei
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Lei Lei
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Advisory Committee
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co-chair
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Qi
NamePart (type = given)
Lian
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Lian Qi
Affiliation
Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Wang
NamePart (type = given)
ShengBin
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ShengBin Wang
Affiliation
Advisory Committee
Role
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outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - Newark
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
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2017-05
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2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Abundant and real-time data from manufacturing and healthcare industries opens up opportunities previously unimaginable to capture fast changing customer bases, identify new sources of profit, and devise personalized medicine. This thesis consists of three essays: the first essay develops a machine learning algorithm based on a novel pharmacokinetic pharmacodynamic model for inpatients under warfarin therapy to make personalized predictions on blood clotting times on a rolling horizon. The second essay develops a set of methodologies to detect patterns in the online sales data of a children-shoes manufacturer in China to predict price elasticity. The third essay solves a challenging production scheduling problem in a three-stage supply chain. Specifically, the first essay designs a pharmacokinetic pharmacodynamic model to make individualized and adaptive international normalized ratio (INR) predictions for warfarin inpatients in changing clinical status. We tested a new model on 60 inpatients at Columbia Medical Center. The model personalizes four submodels and minimizes the number of parameters to be estimated. Prediction accuracy was assessed by prediction error, absolute prediction error and percentage absolute prediction error. The INRs (International Normalized Ratio, to measure blood clotting times) were accurately predicted 5 days into the future. Median prediction error: 0.01–0.12; median absolute prediction error: 0.17–0.5 and median percentage absolute prediction error: 9.85–26.06%. Patients exhibit interindividual and intertemporal variability. The model captures the variability and provides accurate and personalized INR predictions. In the second essay, we study the problem of pricing and promotion for an online seller of children shoes and try to estimate the price elasticity for different products at different seasons. By testing the various models to capture the seasonality, price elasticity and sales inertia, we may accurately forecast the sales lift for various price discounts, so as to provide a foundation for data-driven price / promotion optimization. In the third essay, we study a three-stage supply chain, where the second stage refers to the operations of external contracted manufacturers. The external manufacturers each has multiple time windows in which the resources needed for the outsourced operation are available. Both internal and external operations are non-instantaneous, and the required processing times are subject to various resource constraints. The problem is to assign and sequence a given set of customer orders to both the internal and the external processes so the total tardiness in the order fulfillment is minimized. We present mathematical models that define different variations of this problem, analyze the special cases that can be solved in polynomial times, and then develop heuristic algorithms that can be applied to quickly solve the problems with a reasonable quality. In particular, we show that a heuristic solution based on the 3D linear assignment algorithm has a potential to be an effective approach for this type of problems.
Subject (authority = RUETD)
Topic
Management
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_7994
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xii, 97 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Business logistics
Subject (authority = ETD-LCSH)
Topic
Health services administration--Data processing
Note (type = statement of responsibility)
by Yijun Wang
RelatedItem (type = host)
TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
Identifier (type = local)
rucore10002600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3SF304N
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Wang
GivenName
Yijun
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-04-12 12:34:43
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Name
Yijun Wang
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Affiliation
Rutgers University. Graduate School - Newark
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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 (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2019-05-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 31st, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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