Polyhedral Approaches to Hypergraph Partitioning and Cell Formation

buir.advisorAkgül, Mustafa
dc.contributor.authorKandiller, Levent
dc.date.accessioned2016-01-08T20:20:48Z
dc.date.available2016-01-08T20:20:48Z
dc.date.issued1994
dc.descriptionAnkara : Department of Industrial Engineering and Institute of Engineering and Science, Bilkent University, 1994.en_US
dc.descriptionThesis (Ph.D.) -- -Bilkent University, 1994.en_US
dc.descriptionIncludes bibliographical references leaves 152-161en_US
dc.description.abstractHypergraphs are generalizations of graphs in the sense that each hyperedge can connect more than two vertices. Hypergraphs are used to describe manufacturing environments and electrical circuits. Hypergraph partitioning in manufacturing models cell formation in Cellular Manufacturing systems. Moreover, hypergraph partitioning in VTSI design case is necessary to simplify the layout problem. There are various heuristic techniques for obtaining non-optimal hypergraph partitionings reported in the literature. In this dissertation research, optimal seeking hypergraph partitioning approaches are attacked from polyhedral combinatorics viewpoint. There are two polytopes defined on r-uniform hypergraphs in which every hyperedge has exactly r end points, in order to analyze partitioning related problems. Their dimensions, valid inequality families, facet defining inequalities are investigated, and experimented via random test problems. Cell formation is the first stage in designing Cellular Manufacturing systems. There are two new cell formation techniques based on combinatorial optimization principles. One uses graph approximation, creation of a flow equivalent tree by successively solving maximum flow problems and a search routine. The other uses the polynomially solvable special case of the one of the previously discussed polytopes. These new techniques are compared to six well-known cell formation algorithms in terms of different efficiency measures according to randomly generated problems. The results are analyzed statistically.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T20:20:48Z (GMT). No. of bitstreams: 1 1.pdf: 78510 bytes, checksum: d85492f20c2362aa2bcf4aad49380397 (MD5)en
dc.description.statementofresponsibilityKandiller, Leventen_US
dc.format.extent162 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/18603
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectPolyhedral combinatoricsen_US
dc.subjectHypergraph partitioningen_US
dc.subjectCellular manufacturing systemsen_US
dc.subject.lccQA402.5 .K36 1994en_US
dc.subject.lcshCombinatorial optimization.en_US
dc.subject.lcshCombinatorial analysisen_US
dc.subject.lcshPolyhedra.en_US
dc.subject.lcshHypergraph.en_US
dc.subject.lcshManufacturing cells.en_US
dc.titlePolyhedral Approaches to Hypergraph Partitioning and Cell Formationen_US
dc.typeThesisen_US
thesis.degree.disciplineIndustrial Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelDoctoral
thesis.degree.namePh.D. (Doctor of Philosophy)

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