A Gilmore-Gomory Construction of Integer Programming Value Functions

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dc.contributor.advisorSchaefer, Andrew J.
dc.creatorBrown, Seth
dc.date.accessioned2021-05-03T20:56:55Z
dc.date.available2021-05-03T20:56:55Z
dc.date.created2021-05
dc.date.issued2021-04-28
dc.date.submittedMay 2021
dc.date.updated2021-05-03T20:56:56Z
dc.description.abstractIn this thesis, we analyze how sequentially introducing decision variables into an integer program (IP) affects the value function and its level sets. We use a Gilmore-Gomory approach to find parametrized IP value functions over a restricted set of variables. We introduce the notion of maximal connected \color{black}subsets of level sets - volumes in which changes to the constraint right-hand side have no effect on the value function - and relate these structures to IP value functions and optimal solutions.
dc.format.mimetypeapplication/pdf
dc.identifier.citationBrown, Seth. "A Gilmore-Gomory Construction of Integer Programming Value Functions." (2021) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/110397">https://hdl.handle.net/1911/110397</a>.
dc.identifier.urihttps://hdl.handle.net/1911/110397
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectValue function
dc.subjectlevel set
dc.subjectparametrized optimization
dc.titleA Gilmore-Gomory Construction of Integer Programming Value Functions
dc.typeThesis
dc.type.materialText
thesis.degree.departmentComputational and Applied Mathematics
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Arts
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