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dc.contributor.advisorYıldırım, Emre Alperen_US
dc.contributor.authorPaç, A. Buraken_US
dc.date.accessioned2016-01-08T18:18:10Z
dc.date.available2016-01-08T18:18:10Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/11693/15413
dc.descriptionAnkara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2010.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2010.en_US
dc.descriptionIncludes bibliographical references leaves 69-77.en_US
dc.description.abstractIn this study, row generation techniques are applied on general linear programming problems with a very large number of constraints with respect to the problem dimension. A lower bound is obtained for the change in the objective value caused by the generation of a specific row. To achieve row selection that results in a large shift in the feasible region and the objective value at each row generation iteration, the lower bound is used in the comparison of row generation candidates. For a warm-start to the solution procedure, an effective selection of the subset of constraints that constitutes the initial LP is considered. Several strategies are discussed to form such a small subset of constraints so as to obtain an initial solution close to the feasible region of the original LP. Approximation schemes are designed and compared to make possible the termination of row generation at a solution in the proximity of an optimal solution of the input LP. The row generation algorithm presented in this study, which is enhanced with a warm-start strategy and an approximation scheme is implemented and tested for computation time and the number of rows generated. Two efficient primal simplex method variants are used for benchmarking computation times, and the row generation algorithm appears to perform better than at least one of them especially when number of constraints is large.en_US
dc.description.statementofresponsibilityPaç, A Buraken_US
dc.format.extentix, 77 leavesen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRow generationen_US
dc.subjectsimplex methoden_US
dc.subjectclusteringen_US
dc.subject.lccT57.74 .P33 2010en_US
dc.subject.lcshLinear programming.en_US
dc.subject.lcshCluster analysis--Data processing.en_US
dc.subject.lcshAlgorithms.en_US
dc.titleRow generation techniques for approximate solution of linear programming problemsen_US
dc.typeThesisen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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