Branch-decomposition heuristics for linear matroids

dc.contributor.advisorHicks, Illya V.
dc.creatorMa, Jing
dc.date.accessioned2011-07-25T02:07:21Z
dc.date.available2011-07-25T02:07:21Z
dc.date.issued2010
dc.description.abstractThis thesis present two new heuristics which utilize classification and max-flow algorithm respectively to derive near-optimal branch-decompositions for linear matroids. In the literature, there are already excellent heuristics for graphs, however, no practical branch-decomposition methods for general linear matroids have been addressed yet. Introducing a "measure" which compares the "similarity" of elements of a linear matroid, this work reforms the linear matroid into a similarity graph. Then, two different methods, classification method and max-flow method, both basing on the similarity graph are developed into heuristics. Computational results using the classification method and the max-flow method on linear matroid instances are shown respectively.
dc.format.mimetypeapplication/pdf
dc.identifier.callnoTHESIS MATH.SCI. 2010 MA
dc.identifier.citationMa, Jing. "Branch-decomposition heuristics for linear matroids." (2010) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/62192">https://hdl.handle.net/1911/62192</a>.
dc.identifier.urihttps://hdl.handle.net/1911/62192
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.subjectApplied mathematics
dc.subjectMathematics
dc.titleBranch-decomposition heuristics for linear matroids
dc.typeThesis
dc.type.materialText
thesis.degree.departmentMathematical Sciences
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Arts
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