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Process operations with uncertainty and integration considerations
Descriptive
TypeOfResource
Text
TitleInfo
(ID = T-1)
Title
Process operations with uncertainty and integration considerations
Identifier
ETD_2596
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000053117
Language
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eng
Genre
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theses
Subject
(ID = SBJ-1);
(authority = RUETD)
Topic
Chemical and Biochemical Engineering
Subject
(ID = SBJ-2);
(authority = ETD-LCSH)
Topic
Production planning--Mathematical models
Subject
(ID = SBJ-3);
(authority = ETD-LCSH)
Topic
Production scheduling--Mathematical models
Abstract
(type = abstract)
There has been a lot of attention in recent years towards the application of mathematical modeling and optimization approaches for the solution of production planning and scheduling problems. This is mainly due to the changing economic environment which pushes for more efficient process operations. However, there are still a number of challenges that restrict the effective application of optimization for planning and scheduling problem especially in the process industry. First, decision making in process operations is frequently based on parameters of which the values are uncertain. A systematic treatment of those uncertainties (e.g., processing time variations, rush orders, failed batches, machine breakdowns, etc) is necessary to satisfy the customer demands, increase the efficiency of operations and improve the plant profitability. Moreover, the interactions between the different decision-making levels were often ignored in existing solution approaches, which leads to sub-optimal and even infeasible solutions. Thus the integration of different decision making levels has been recognized by the research community as an imperative problem. In this work, systematic methods have been developed to address the above challenges. First, different methodologies are proposed to address the uncertainties in process scheduling problem: robust optimization based preventive scheduling strategy which aims at generating a robust preventive schedule to handle the possible parameter perturbations; parametric programming based reactive scheduling strategy which aims at responsive schedule regeneration or updating upon the happening of disruptive events. To address the interaction between planning and scheduling decision levels, a dual decomposition based approach that targets the solution of large scale planning and scheduling integration problem was proposed, which aims at decreasing the computational complexity through decomposition and parallel computation. Finally, the rolling horizon method which provides a promising modeling framework for integrated planning and scheduling and incorporation of uncertainty is studied. A novel method of generating production capacity model through parametric programming technique is proposed, and it is verified that the incorporation of the capacity model into the rolling horizon framework can improve the solution quality.
PhysicalDescription
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electronic resource
Extent
xii, 136 p. : ill.
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application/pdf
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text/xml
Note
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Ph.D.
Note
Includes abstract
Note
Vita
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(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Zukui Li
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Li
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Zukui
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1981-
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author
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Zukui Li
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Ierapetritou
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Marianthi G.
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chair
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Advisory Committee
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Marianthi G. Ierapetritou
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Androulakis
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Ioannis P.
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internal member
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Advisory Committee
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Ioannis P. Androulakis
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NamePart
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Chiew
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Yee C.
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internal member
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Advisory Committee
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Yee C. Chiew
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NamePart
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Coit
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David W.
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outside member
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Advisory Committee
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David W. Coit
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NamePart
Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
Role
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school
OriginInfo
DateCreated
(qualifier = exact)
2010
DateOther
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(type = degree)
2010
Place
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(type = code)
xx
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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
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rucore19991600001
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NjNbRU
Identifier
(type = doi)
doi:10.7282/T3VX0GKK
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
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(ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder
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(type = personal)
Name
FamilyName
Li
GivenName
Zukui
Role
Copyright Holder
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Type
Permission or license
DateTime
2010-04-13 22:22:43
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Name
Zukui Li
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.
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Technical
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ETD
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application/pdf
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application/x-tar
FileSize
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2058240
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