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On Solving Selected Nonlinear Integer Programming Problems in Data Mining, Computational Biology, and Sustainability

Trapp, Andrew Christopher (2011) On Solving Selected Nonlinear Integer Programming Problems in Data Mining, Computational Biology, and Sustainability. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

This thesis consists of three essays concerning the use of optimization techniques to solve four problems in the fields of data mining, computational biology, and sustainable energy devices. To the best of our knowledge, the particular problems we discuss have not been previously addressed using optimization, which is a specific contribution of this dissertation. In particular, we analyze each of the problems to capture their underlying essence, subsequently demonstrating that each problem can be modeled as a nonlinear (mixed) integer program. We then discuss the design and implementation of solution techniques to locate optimal solutions to the aforementioned problems. Running throughout this dissertation is the theme of using mixed-integer programming techniques in conjunction with context-dependent algorithms to identify optimal and previously undiscovered underlying structure.

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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Trapp, Andrew Christopheract25@pitt.eduACT25
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairProkopyev, Oleg A.prokopyev@engr.pitt.eduDROLEG
Committee MemberSchaefer, Andrew J.schaefer@pitt.eduSCHAEFER
Committee MemberCamacho, Carlos J.ccamacho@pitt.eduCCAMACHO
Committee MemberRajgopal, Jayantrajgopal@engr.pitt.eduGUNNER1
Committee MemberVielma, Juan Pablojvielma@pitt.eduJVIELMA
Date: 27 June 2011
Date Type: Completion
Defense Date: 3 March 2011
Approval Date: 27 June 2011
Submission Date: 22 February 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Industrial Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: algorithm; computational biology; data mining; integer programming; nonlinear; operations research; optimization; sustainability
Other ID: http://etd.library.pitt.edu/ETD/available/etd-02222011-131629/, etd-02222011-131629
Date Deposited: 10 Nov 2011 19:31
Last Modified: 15 Nov 2016 13:36
URI: http://d-scholarship.pitt.edu/id/eprint/6394

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