Branch-decomposition heuristics for linear matroids

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dc.contributor.advisorHicks, Illya V.en_US
dc.creatorMa, Jingen_US
dc.date.accessioned2011-07-25T02:07:21Zen_US
dc.date.available2011-07-25T02:07:21Zen_US
dc.date.issued2010en_US
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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS MATH.SCI. 2010 MAen_US
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>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/62192en_US
dc.language.isoengen_US
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.en_US
dc.subjectApplied mathematicsen_US
dc.subjectMathematicsen_US
dc.titleBranch-decomposition heuristics for linear matroidsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Artsen_US
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